Devices, methods, and computer programs for decoding encoded audio signals.

Abstract

An apparatus, method and computer program for decoding an encoded audio signal are provided. The apparatus for decoding an encoded audio signal including an encoded core signal and parameterized data comprises: a core decoder (600) for decoding the encoded core signal to obtain a decoded core signal; an analyzer (602) for analyzing the decoded core signal before or after performing a frequency regeneration operation to provide an analysis result (603); and a frequency regenerator (604) for regenerating a spectral portion not included in the decoded core signal using a spectral portion of the decoded core signal, parameterized data (605) and the analysis result (603).

Description

[0001] This patent application is a divisional application of a patent application with an international application date of July 15, 2014, a national application number of 201480041246.1, and an invention name of "Device, method and computer program for decoding encoded audio signals". Technical Field

[0002] The present invention relates to audio encoding / decoding, and in particular to audio coding using intelligent gap filling (IGF). Background Art

[0003] Audio coding is a signal compression field that uses psychoacoustic knowledge to process redundant and irrelevant parts in audio signals. Today, audio codecs usually require about 60kbps / channel to perform perceptually transparent encoding of almost any type of audio signal. Newer codecs are designed to reduce the encoding bit rate by utilizing the spectral similarity in the signal using technologies such as bandwidth extension (BWE). The BWE scheme uses a low bit rate parameter set to represent the high frequency (HF) component of the audio signal. The HF spectrum is filled with spectral content from the low frequency (LF) region, and the spectral shape, tilt, and time domain continuity are adjusted to maintain the sound quality and timbre of the original signal. Such a BWE method enables the audio codec to maintain good quality even at a low bit rate of about 24kbps / channel.

[0004] The audio coding system of the present invention efficiently encodes arbitrary audio signals at a wide variety of bit rates. However, for high bit rates, the system of the present invention converges to transparency, and for low bit rates, perceptual annoyance is minimized. Therefore, the main share of the available bit rate in the encoder is used to waveform encode only the most perceptually relevant structures of the signal, and in the decoder the resulting spectral gaps are filled with roughly approximated signal content of the original spectrum. The so-called spectrally intelligent gap filling (IGF), which is parameter-driven and controlled by dedicated side information sent from the encoder to the decoder, consumes only a very limited bit budget.

[0005] The storage or transmission of audio signals is often subject to strict bit rate constraints. In the past, encoders were forced to drastically reduce the transmission audio bandwidth when only very low bit rates were available.

[0006] Modern audio codecs are now able to encode wideband signals by using bandwidth extension (BWE) methods [1]. These algorithms rely on a parameterized representation of the high frequency content (HF), which is generated from a waveform-coded low frequency part (LF) by means of a transfer ("patching") to the HF spectral region, and the application of parameter-driven post-processing. According to the BWE scheme, the reconstruction of the HF spectral region above a given so-called crossover frequency is usually based on spectral patching. Typically, the HF region comprises a plurality of adjacent patches, and each of these patches originates from a bandpass (BP) region of the LF spectrum below a given crossover frequency. Prior art systems efficiently perform patching within a filter bank representation, such as a quadrature mirror filter bank (QMF), by copying a set of adjacent subband coefficients from a source region to a target region.

[0007] Another technique found in today's audio codecs to improve compression efficiency and thus enable extension of audio bandwidth at low bit rates is parameter-driven synthetic replacement of appropriate portions of the audio spectrum. For example, noise-like signal portions of the original audio signal can be replaced with artificial noise generated in the decoder and scaled by side information parameters, with substantially no loss in subjective quality. An example is the Perceptual Noise Substitution (PNS) tool included in MPEG-4 Advanced Audio Coding (AAC) [5].

[0008] Another technique that also enables the extension of audio bandwidth at low bit rates is the noise filling technique included in MPEG-D Unified Speech and Audio Coding (USAC) [7]. The spectral gaps (zeros) inferred by the dead zones of the quantizer due to too coarse quantization are then filled with artificial noise in the decoder and scaled by parameter-driven post-processing.

[0009] Another prior art system is known as exact spectral replacement (ASR) [2-4]. In addition to the waveform codec, ASR employs a dedicated signal synthesis stage which restores the perceptually important sinusoidal part of the signal at the decoder. Furthermore, the system described in [5] relies on sinusoidal modeling in the HF region of the waveform coder to enable extended audio bandwidth with decent perceptual quality at low bit rates. All of these approaches involve transforming the data to a second domain other than the modified discrete cosine transform (MDCT) and also involve fairly complex analysis / synthesis stages for preserving the HF sinusoidal components.

[0010] FIG. 13A shows a schematic diagram of an audio encoder for a bandwidth extension technique such as used in, for example, high-efficiency advanced audio coding (HE-ACC). The audio signal at line 1300 is input to a filter system comprising a low-pass filter 1302 and a high-pass filter 1304. The signal output by the high-pass filter 1304 is input to a parameter extractor / encoder 1306. The parameter extractor / encoder 1306 is configured to calculate and encode parameters such as, for example, spectrum envelope parameters, noise addition parameters, lost harmonic parameters or inverse filtering parameters. These extracted parameters are input to a bitstream multiplexer 1308. The low-pass output signal is input to a processor that generally includes the functions of a downsampler 1310 and a core encoder 1312. The bandwidth to be encoded by low-pass 1302 is limited to a bandwidth that is significantly smaller than the bandwidth that appears in the original input audio signal on line 1300. This provides a significant coding gain due to the fact that all functions that appear in the core encoder only have to operate on signals with reduced bandwidth. When, for example, the bandwidth of the audio signal on line 1300 is 20 kHz and when the low-pass filter 1302 has a bandwidth of, for example, 4 kHz, in order to satisfy the sampling theorem, it is theoretically sufficient that the sampling frequency of the signal after the downsampler is 8 kHz, which is essentially reduced to the required sampling rate of the audio signal 1300, which must be at least 40 kHz.

[0011] Figure 13 B shows the schematic diagram of corresponding bandwidth extension decoder.Decoder comprises bitstream multiplexer 1320.Bitstream demultiplexer 1320 extracts the input signal of core decoder 1322 and the input signal of parameter decoder 1324.In the example above, the sampling rate of core decoder output signal is 8kHz and therefore bandwidth is 4kHz, yet, for complete bandwidth reconstruction, the output signal of high frequency reconstruction device 1330 must be in 20kHz, and it requires the sampling rate of at least 40kHz.In order to make this possible, need to have the decoder processor of the function of up sampler 1325 and filter bank 1326.Then, high frequency reconstruction device 1330 receives the low frequency signal through frequency analysis output by filter bank 1326, and uses the parameterization of high frequency band to represent that the frequency range limited by the high pass filter 1304 of Figure 13 A is reconstructed. The high frequency reconstructor 1330 has several functions such as using the source range in the low frequency range to regenerate the upper frequency range, spectrum envelope adjustment, noise addition function and the function of introducing lost harmonics in the upper frequency range, and in order to explain the fact that the higher frequency range usually has a different tone from the lower frequency range, if applied and calculated in the encoder of Figure 13A, an inverse filtering operation is also included. In HE-ACC, the lost harmonics are resynthesized on the decoder side and are accurately placed in the middle of the reconstruction band. Therefore, all the lost harmonic lines determined in a certain reconstruction band are not placed at the frequency value located in the original signal. Instead, those lost harmonic lines are placed at the frequency within the center of a certain band. Thus, when the lost harmonic line in the original signal is placed very close to the reconstruction band boundary in the original signal, the error of the frequency introduced by placing the lost harmonic line in the reconstructed signal at the center of the band is close to 50% of the individual reconstruction bands for which the parameters are generated and sent.

[0012] Furthermore, while a typical audio core encoder operates in the spectral domain, the core decoder generates a time domain signal which is then converted back to the spectral domain by the filter bank 1326 function. This introduces additional processing delays, may introduce artifacts due to the cascade of first transforming from the spectral domain to the frequency domain and back again to the generally different frequency domain, and of course requires a great deal of computational complexity and therefore power, which is particularly an issue when the bandwidth extension technique is applied to mobile devices such as mobile phones, tablets or laptops etc.

[0013] Current audio codecs use BWE as an integral part of the coding scheme to perform low bitrate audio coding. However, BWE techniques are limited to replacing only high frequency (HF) content. Furthermore, they cannot enable perceptually important content above a given crossover frequency to be waveform encoded. Therefore, since the precise alignment of the pitch harmonics of the signal is not considered in most systems, contemporary audio codecs lose HF details or timbre when implementing BWE.

[0014] Another disadvantage of current prior art BWE systems is the need to transform the audio signal into a new domain to implement BWE (eg, from the MDCT domain to the QMF domain). This results in synchronization complications, additional computational complexity, and increased storage requirements.

[0015] The storage or transmission of audio signals is often subject to strict bit rate constraints. In the past, encoders were forced to significantly reduce the transmission audio bandwidth when only very low bit rates were available. Modern audio codecs are now able to encode wideband signals by using bandwidth extension (BWE) methods [1-2]. These algorithms rely on a parameterized representation of the high frequency content (HF), which is generated from the waveform-encoded low frequency part (LF) of the decoded signal by means of a transfer ("patching") to the HF spectral region, and the application of parameter-driven post-processing.

[0016] According to the BWE scheme, the reconstruction of the HF spectral region above a given so-called crossover frequency is usually based on spectral patching. Other schemes for filling the spectral gaps, such as intelligent gap filling (IGF), use adjacent so-called spectral tiles to regenerate parts of the HF spectrum of the audio signal. Typically, the HF region includes a plurality of adjacent patches or tiles, and each of these patches or tiles originates from a bandpass (BP) region of the LF spectrum below a given crossover frequency. Prior art systems efficiently perform patching or tiling within a filter bank representation by copying a set of adjacent subband coefficients from a source region to a target region. However, for some signal contents, the assembly of the reconstructed signal from adjacent patches within the LF band and the HF band can lead to beats, misalignment, and audible roughness.

[0017] Thus, in

[19] , the concept of detuning guardband filtering emerged in the context of filter-bank based BWE systems. It was suggested to effectively apply a notch filter of approximately 1 bark bandwidth at the crossover frequency between the LF and the BWE regenerated HF to avoid the possibility of detuning and replace the spectral content with zero signal or noise.

[0018] However, the solution proposed in

[19] has some disadvantages: First, strictly replacing the spectral content with either zero signal or noise may also impair the perceived quality of the signal. In addition, the proposed processing is not signal adaptive and may therefore impair the perceived quality in some cases. For example, if the signal contains transient signals, this may result in pre-echoes and post-echoes.

[0019] Secondly, detuning may also occur at the transition between consecutive HF patches. The solution proposed in

[19] is only intended to remedy the detuning that occurs at the crossover frequency between the LF and the BWE regenerated HF.

[0020] Finally, unlike filter bank based systems as proposed in

[19] , BWE systems can also be implemented in transform based implementations such as, for example, the modified discrete cosine transform (MDCT). Transforms such as the MDCT are very susceptible to so called warble

[20] or ringing artifacts which occur when the passband region of the spectral coefficients is copied or the spectral coefficients are set to zero as proposed in

[19] .

[0021] Specifically, U.S. Pat. No. 8,412,365 discloses the use of inserted so-called guard bands consisting of one or several sub-band channels set to zero in filter bank based conversion or folding. Multiple filter bank channels are used as guard bands, and the bandwidth of the guard bands should be 0.5 bark. These detuned guard bands are partially reconstructed using random white noise signals, i.e., these sub-bands are filled with white noise instead of zero signals. The guard bands are inserted independently of the current signal to be processed. Summary of the invention

[0022] It is an object of the present invention to provide an improved concept for decoding a coded audio signal.

[0023] The object is achieved by a device for decoding a coded audio signal, a method for decoding a coded audio signal, or a computer-readable medium.

[0024] According to the present invention, decoder-side signal analysis using an analyzer is performed to analyze the decoded core signal before or after performing a frequency regeneration operation to provide an analysis result. The analysis result is then used by the frequency regenerator to regenerate a portion of the spectrum not included in the decoded core signal.

[0025] Thus, in contrast to a fixed decoder setup, wherein patching or frequency tiling is performed in a fixed manner, i.e. wherein a certain source range is taken from the core signal and certain fixed frequency boundaries are imposed to set the frequency between the source range and the reconstruction range or to set the frequency boundaries between two adjacent frequency patches or tiles within the reconstruction range, a signal-dependent patching or tiling is performed, wherein, for example, the core signal can be analyzed to find local minima in the core signal and then the core range is selected such that the frequency boundaries of the core range coincide with local minima in the core signal spectrum.

[0026] Alternatively or additionally, a signal analysis may be performed on a preliminary regenerated signal or a preliminary frequency patched or tiled signal, wherein, after the preliminary frequency regeneration process, the boundary between the core range and the reconstruction range is analyzed to detect any artifact-generating signal portions, such as problematic tonal portions that generate beat artifacts due to their close proximity to each other when reconstructed. Alternatively or additionally, the boundary may also be checked in the following manner: mid-clip of a tonal portion is detected, and this clipping of a tonal portion may still cause artifacts when reconstructed. In order to avoid these processes, the frequency boundary between two separate frequency tiles or patches in the reconstruction range and / or source range and / or reconstruction range may be modified by a signal operator to perform reconstruction again with the newly set boundary.

[0027] Additionally or alternatively, the frequency regeneration is a regeneration based on the analysis results, in that the frequency boundaries are preserved as is and problematic tonal portions close to the frequency boundaries between the source range and the reconstruction range or between two separate frequency tiles or patches within the reconstruction range are eliminated or at least attenuated. Such tonal portions may be close tones, which may result in beat artifacts or may be tonal portions that are clipped midway.

[0028] Specifically, when using non-energy-saving transformations such as MDCT, a single tone is not directly mapped to a single spectral line. Alternatively, a single tone will be mapped to a group of spectral lines with a certain amplitude depending on the pitch phase. When the patching operation clips the tone portion, even if perfect reconstruction is implemented as in the MDCT reconstructor, this will still cause artifacts after reconstruction. This is due to the following fact: the MDCT reconstructor will need the complete pitch pattern of the tone to correctly reconstruct the tone in the end. Since clipping has occurred before, this is no longer possible, and therefore a time-varying tremolo artifact will be created. Based on the analysis according to the present invention, the frequency regenerator will cause the complete tone portion of the artifact by attenuation, or as discussed above by changing the corresponding boundary frequency, or by applying two measurements, or by even reconstructing the clipped part based on a certain foreknowledge of such a tone pattern, to avoid this situation.

[0029] Additionally or alternatively, cross filtering may be applied to spectrally cross filtering the decoded core signal and a first frequency tile extending in frequency from a gap filling frequency to a first tile stop frequency, or to spectrally cross filtering the first frequency tile and a second frequency tile.

[0030] This crossover filtering is useful to reduce so-called filter ringing.

[0031] The method of the invention is primarily intended to be applied in BWE based on transforms such as MDCT. However, the teachings of the invention are generally applicable, for example, similarly within systems based on quadrature mirror filters (QMF), especially if the system is critically sampled, such as a real-valued QMF representation.

[0032] The method of the present invention is based on the observation that auditory harshness, beats and dissonances may only occur when the signal content in frequency domain regions close to transition points (such as crossover frequencies or patch boundaries) is very tonal. Therefore, a solution proposed to the shortcomings found in the prior art includes signal adaptive detection of tonal components in the transition region and subsequent attenuation or removal of these components. Preferably, the attenuation or removal of these components can be accomplished by bottom-to-bottom spectral interpolation of such components or, alternatively, by zero signal or noise insertion. Alternatively, the spectral position of the transition can be signal adaptively selected so that transition artifacts are minimized.

[0033] In addition, this technique can be used to reduce or even avoid filter ringing. Especially for transient-like signals, ringing is an audible and annoying artifact. Filter ringing artifacts are caused by the so-called brick-wall characteristics of the filter in the transition band (steep transition from passband to stopband at the cutoff frequency). Such filters can be efficiently implemented by setting one coefficient or multiple groups of coefficients to zero in the frequency domain of the time-frequency transform. Therefore, in the case of BWE, it is recommended to apply a crossover filter at each transition frequency between patches or between the core band and the first patch to reduce the above-mentioned ringing effect. The crossover filter can be implemented by adopting spectral weighting with a suitable gain function in the transform domain.

[0034] According to another aspect of the present invention, an apparatus for decoding an encoded audio signal comprises: a core decoder; a tile generator for generating one or more spectral tiles having frequencies not included in the decoded core signal using a spectral portion of a decoded core signal; and a crossover filter for spectrally cross-filtering the decoded core signal and a first frequency tile having a frequency extending from a gap-filling frequency to a first tile stop frequency, or for spectrally cross-filtering a certain tile and another frequency tile having a lower boundary frequency adjacent to an upper boundary frequency of the certain frequency tile.

[0035] Preferably, the process is intended to be applied in bandwidth extension based on transforms such as MDCT. However, the invention is generally applicable and in particular in bandwidth extension scenarios based on quadrature mirror filter banks (QMF), especially if the system is critically sampled, for example when there is a real-valued QMF representation as a time-frequency transform or as a frequency-time transform.

[0036] This embodiment is particularly useful for transient-like signals, for which ringing is an audible and annoying artifact. Filter ringing artifacts are caused by the so-called brick-wall characteristic of the filter in the transition band, i.e., the steep transition from the passband to the stopband at the cut-off frequency. Such filters can be efficiently implemented by setting one coefficient or multiple groups of coefficients to zero in the frequency domain of the time-frequency transform. Therefore, the present invention relies on crossover filters at each transition frequency between patches / tiles or between the core band and the first patch / tile to reduce the ringing artifact. Preferably, the crossover filters are implemented by spectral weighting using a suitable gain function in the transform domain.

[0037] Preferably, the crossover filter is signal adaptive and comprises two filters, a fade-out filter applied to the low spectral region and a fade-in filter applied to the high spectral region. The filters may be symmetrical or asymmetrical depending on the specific implementation.

[0038] In another embodiment, the frequency tiles or frequency patches are not only subjected to cross-filtering, but preferably, before performing the cross-filtering, the tile generator performs patch adaptation, which includes setting frequency boundaries at spectral minima and removing or attenuating tonal portions remaining in the transition range around the transition frequencies. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Preferred embodiments are discussed below with reference to the accompanying drawings, in which:

[0040] Figure 1A An apparatus for encoding an audio signal is shown;

[0041] Figure 1B Shown with Figure 1A A decoder matched with the encoder for decoding the encoded audio signal;

[0042] Figure 2A A preferred implementation of a decoder is shown;

[0043] Figure 2B A preferred implementation of the encoder is shown;

[0044] Figure 3A Shown by Figure 1B Schematic representation of the spectrum generated by the spectral domain decoder of;

[0045] Figure 3B A table showing the relationship between the scale factor of the scale factor band and the energy used to reconstruct the band and the noise filling information of the noise filling band;

[0046] Figure 4A The functionality of a spectral domain encoder for applying the selection of spectral portions to a first group of spectral portions and a second group of spectral portions is shown;

[0047] Figure 4B Shows Figure 4A The realization of the function;

[0048] Figure 5A shows the functionality of the MDCT encoder;

[0049] Figure 5B shows the functionality of a decoder using MDCT technology;

[0050] Figure 5C shows the implementation of a frequency regenerator;

[0051] Fig. 6A is a device for decoding a coded audio signal according to an implementation;

[0052] Figure 6B is another embodiment of an apparatus for decoding an encoded audio signal;

[0053] Fig. 7A Shows Fig. 6A or Figure 6B Optimal implementation of a frequency regenerator;

[0054] Figure 7B Another implementation of cooperation between the analyzer and the frequency regenerator is shown;

[0055] Fig. 8A Another implementation of a frequency regenerator is shown;

[0056] Figure 8B Another embodiment of the present invention is shown;

[0057] Fig.9A A decoder having a frequency regeneration technique using energy values ​​of a regeneration frequency range is shown;

[0058] Fig. 9B Shows Fig.9A A more detailed implementation of the frequency regenerator;

[0059] Fig. 9C Shows Shows Fig. 9B Schematic diagram of the function;

[0060] Fig.9D Shows Fig.9A Yet another implementation of the decoder;

[0061] Fig. 10A Shown with Fig.9A The decoder matches the encoder block diagram;

[0062] Fig. 10B Shown for illustration Fig. 10A A block diagram of yet another function of a parameter calculator;

[0063] Fig. 10C Shows Shows Fig. 10A A block diagram of yet another function of a parameterized calculator;

[0064] Fig. 10D Shows Fig. 10A A block diagram of yet another function of a parameterized calculator;

[0065] Fig.11A shows the spectrum of filter ringing around a transient signal;

[0066] Fig. 11B shows a spectrum diagram of a transient signal after bandwidth extension is applied;

[0067] Fig. 11C shows a spectrum plot of a transient signal after applying bandwidth extension with filter ringing suppression;

[0068] Fig. 12A A block diagram of an apparatus for decoding an encoded audio signal is shown;

[0069] Fig. 12B shows the amplitude spectra (stylized) of a tonal signal, a copy without patch / tile adaptation, a copy with altered frequency boundaries, and additional elimination of the artifact-producing tonal parts;

[0070] Fig. 12C An example cross-fade function is shown;

[0071] FIG13A shows a prior art encoder with bandwidth extension;

[0072] FIG13B shows a prior art decoder with bandwidth extension;

[0073] Fig.14A Another apparatus for decoding an encoded audio signal using a crossover filter is shown; and

[0074] Fig. 14B A more detailed diagram of an exemplary crossover filter is shown. DETAILED DESCRIPTION

[0075] Fig. 6AA device for decoding an encoded audio signal including an encoded core signal and parameterized data is shown. The device includes a core decoder 600 for decoding the encoded core signal to obtain a decoded core signal, and an analyzer 602 for analyzing the decoded core signal before or after performing a frequency regeneration operation. The analyzer 602 is configured to provide an analysis result 603. A frequency regenerator 604 is configured to regenerate a spectral portion not included in the decoded core signal using a spectral portion of the decoded core signal, envelope data 605 of the lost spectral portion, and the analysis result 603. Therefore, compared with earlier implementations, frequency regeneration is not performed signal-independently on the decoder side, but rather signal-dependently. This has the following advantages: when there is no problem, frequency regeneration is performed as is, but when there is a problematic signal portion, this is detected by the analysis result 603, and then the frequency regenerator 604 performs an adaptive method for frequency regeneration, which may be a change in the initial frequency boundary between, for example, the core region and the reconstructed frequency band or a change in the frequency boundary between two separate tiles / patches within the reconstructed frequency band. Compared to a guard band implementation, this has the advantage that the specific process is only performed when needed, rather than being performed all the time without any signal correlation as in a guard band implementation.

[0076] Preferably, the core decoder 600 is implemented as Figure 6B The core decoder 600 then outputs the core signal spectrum, and the spectrum is composed of Fig. 6A The analyzer 602 in FIG. 6 is very similar to the spectrum analyzer 614 in FIG. 6 , which is implemented as a spectrum analyzer rather than being implemented as a spectrum analyzer. Fig. 6A Any arbitrary analyzer shown also analyzes time domain signals. Figure 6B In the embodiment of the present invention, the spectrum analyzer is configured to analyze the spectrum signal so that the local minimum in the source frequency band and / or the target frequency band, i.e., the frequency patch or the frequency patch, can be determined. Then, as shown at 616, the frequency regenerator 604 performs the frequency regeneration in which the patch boundary is set to the minimum value in the source frequency band and / or the target frequency band.

[0077] Then, discuss Fig. 7A By description Fig. 6A The preliminary signal regenerator 702 receives as input the source data from the source frequency band and also receives as input the preliminary patch information such as the preliminary boundary frequency. Then, a preliminary regenerated signal 703 is generated which is detected by a detector 704 for detecting the tonal components within the preliminary reconstructed signal 703. Alternatively or additionally, a preliminary regenerated signal 703 may also be generated by a detector 704 for detecting the tonal components within the preliminary reconstructed signal 703. Fig. 6AThe detector corresponding to the analyzer 602 of the source data 705 is used to analyze the source data. Then, the preliminary signal regeneration step will not be necessary. Fig. 12B As discussed, when there is a well-defined mapping from source data to reconstructed data, it is possible to detect minima or tonal parts even by considering only the source data, whether the tonal parts are close to the upper boundary of the core range or at the frequency boundary between two separately generated frequency tiles.

[0078] When a problematic tonal component is found at a frequency boundary, a transition frequency adjuster 706 performs an adjustment of the transition frequency, such as the transition frequency between the core band and the reconstruction band or between the various frequency parts generated by the same source data in the reconstruction band, or the crossover frequency or the gap filling start frequency. The output signal of block 706 is forwarded to a remover 708 of the tonal component at the boundary. The remover is configured to remove the residual tonal component that still exists after the transition frequency adjustment of block 706. Then, the result of the remover 708 is forwarded to a crossover filter 710 to solve the filter ringing problem, and then, the result of the crossover filter 710 is input to a spectral envelope shaping block 712 that performs spectral envelope shaping in the reconstruction band.

[0079] As in Fig. 7A As discussed in the context of , the tonal component detection in block 704 may be performed on either the source data 705 or the preliminary reconstructed signal 703 . Figure 7B An embodiment is shown in which a preliminary regeneration signal is created as shown in block 718. Then, Fig. 7A The signal corresponding to the signal 703 is then forwarded to the detector 720 for detecting the artifact generation component. Although the detector 720 can be configured as Fig. 7A The detector for detecting the tonal component at the frequency boundary shown at 704 in FIG. 1 is a detector for detecting the tonal component at the frequency boundary, but the detector can also be implemented to detect other artifact generation components. Such spectral components can be other components even except the tonal components, and the detection of whether the artifact is generated can be performed by trying different regenerations and comparing the different regeneration results to find out which regeneration provides the artifact generation component.

[0080] The detector 720 now controls an operator 722 for operating the signal, the preliminary regeneration signal. This can be done by actually processing the preliminary regeneration signal by line 723 or by re-performing the regeneration, but now with a modified transition frequency as shown by line 724, for example.

[0081] One implementation of the operation process is as follows Fig. 7A The transition frequency is adjusted as shown at 706 in FIG. Fig. 8A It is shown that block 706 can be replaced or combined with Fig. 7AAnother implementation is performed together with block 706 of . The detector 802 is arranged to detect the starting frequency and the ending frequency of the problematic tone part. Then, the interpolator 804 is configured to interpolate between the starting and the ending of the tone part within the spectrum and preferably perform complex interpolation. Then, as in Fig. 8A As shown in block 806, the tone portion is replaced with the interpolated result.

[0082] Fig. 8A Blocks 808 and 810 in FIG. 8 show an alternative implementation. Instead of performing interpolation, random generation of spectral lines is performed between the beginning and the end of the tonal portion 808. Then, energy adjustment of the randomly generated spectral lines is performed as shown at 810, and the energy of the randomly generated spectral lines is set so that the energy is similar to the adjacent non-tonal spectral portion. The audio portion is then replaced with the envelope-adjusted randomly generated spectral lines. The spectral lines can be randomly generated or pseudo-randomly generated to provide a replacement signal that is as artifact-free as possible.

[0083] Figure 8B Another implementation is shown. At block 820, a Fig. 6A The frequency tile generator in the frequency regenerator 604 is used. The frequency tile generator uses a predetermined frequency boundary. Then, the analyzer analyzes the signal generated by the frequency tile generator, and preferably, the frequency tile generator 820 is configured to perform multiple tiling operations to generate multiple frequency tiles. Then, Figure 8B The operator 824 in the embodiment operates the result of the frequency tile generator according to the analysis result output by the analyzer 822. The operation can be a change in the frequency boundary or an attenuation of each part. Then, the spectrum envelope adjuster 826 uses the frequency spectrum as already described. Fig. 6A spectral envelope adjustment is performed using parameterized information 605 discussed in the context of FIG.

[0084] The spectrally adjusted signal output by block 826 is then input to a frequency-to-time converter which additionally receives a spectral representation of the first spectral portion, ie the output signal of the core decoder 600. The output of the frequency-to-time converter 828 may then be used for storage or for transmission to a speaker for audio presentation.

[0085] The present invention can be applied to a known frequency regeneration process as shown in FIG. 13A and FIG. 13B or preferably, can be applied to a subsequent reference frequency regeneration process. Figures 1A to 5B as well as 9A to 10D In the case of smart gap filling described.

[0086] Figure 1AAn apparatus for encoding an audio signal 99 is shown. The audio signal 99 is input to a time-spectral converter 100 for converting an audio signal having a sampling rate into a spectral representation 101 output by the time-spectral converter. The spectrum 101 is input to a spectrum analyzer 102 for analyzing the spectral representation 101. The spectrum analyzer 101 is configured to determine a first group of first spectral portions 103 to be encoded at a first spectral resolution and a different second group of second spectral portions 105 to be encoded at a second spectral resolution. The second spectral resolution is smaller than the first spectral resolution. The second group of second spectral portions 105 is input to a parameter calculator or parametric encoder 104 for calculating spectral envelope information having a second spectral resolution. In addition, a spectral domain audio encoder 106 is provided for generating a first encoded representation 107 of the first group of first spectral portions having the first spectral resolution. In addition, the parameter calculator / parametric encoder 104 is configured to generate a second encoded representation 109 of the second group of second spectral portions. The first coded representation 107 and the second coded representation 109 are input to a bitstream multiplexer or bitstream former 108 and the block 108 finally outputs the coded audio signal for transmission or storage on a storage device.

[0087] Typically, the first spectrum portion is Figure 3A 306 will be surrounded by two second spectral portions such as 307A and 307B. This is not the case in HEAAC where the core encoder frequency range is band limited.

[0088] Figure 1B Shown with Figure 1A The first encoded representation 107 is input to a spectral domain audio decoder 112 for generating a first decoded representation of a first set of first spectral portions, the decoded representation having a first spectral resolution. Furthermore, the second encoded representation 109 is input to a parametric decoder 114 for generating a second decoded representation of a second set of second spectral portions having a second spectral resolution lower than the first spectral resolution.

[0089] The decoder also includes a frequency regenerator 116 for regenerating a reconstructed second spectral portion with a first spectral resolution using the first spectral portion. The frequency regenerator 116 performs a tile filling operation, i.e., uses a tile or a portion of the first set of first spectral portions and copies the first set of first spectral portions into a reconstruction range or reconstruction band with the second spectral portion, and typically performs spectral envelope shaping or other operations indicated by the second decoded representation output by the parameterized decoder 114, i.e., by using information about the second set of second spectral portions. As shown at the output of the frequency regenerator 116 on line 117, the decoded first set of first spectral portions and the reconstructed second set of spectral portions are input to a spectrum-to-time converter 118, which is configured to convert the first decoded representation and the reconstructed second spectral portion into a time representation 119, which has a certain high sampling rate.

[0090] Figure 2B Shows Figure 1A The audio input signal 99 is input to the Figure 1A The analysis filter bank 220 corresponding to the time-to-spectral converter 100 is then performed in the TNS block 222. Figure 2B The tone masking block corresponds to Figure 1A The input of the spectrum analyzer 102 of may be the full spectrum value when the time domain noise shaping / time domain tile shaping operation is not applied, and may be the spectrum residual value when the TNS operation of block 222 as shown in FIG2B is applied. For a two-channel signal or a multi-channel signal, a joint channel coding 228 may be additionally performed to make Figure 1A The spectral domain encoder 106 may include a joint channel encoding block 228. In addition, an entropy encoder 232 is provided for performing lossless data compression, which is also Figure 1A Part of the spectral domain encoder 106.

[0091] The spectrum analyzer / tone masker 226 separates the output of the TNS block 222 into a core frequency band and a tonal component corresponding to the first set of first spectrum portions 103 and a Figure 1A The block 224 denoted as IGF parameter extraction coding corresponds to the residual component of the second set of second spectral parts 105. Figure 1A The parameterized encoder 104 and the bitstream multiplexer 230 correspond to Figure 1A bit stream multiplexer 108.

[0092] Preferably, the analysis filterbank 222 is implemented as an MDCT (Modified Discrete Cosine Transform filterbank) and is used to transform the signal 99 into the time-frequency domain using a Modified Discrete Cosine Transform used as a frequency analysis tool.

[0093] Preferably, the spectrum analyzer 226 applies pitch masking. The pitch masking estimation segment is used to separate the pitch components in the signal from the noise-like components. This allows the core encoder 228 to encode all pitch components using a psychoacoustic module. The pitch masking estimation segment can be implemented in a number of different ways and is preferably implemented as a sinusoidal trajectory estimation segment [8, 9] similar in functionality to the sinusoidal modeling of speech / audio coding or the HILN model-based audio encoder described in

[10] . Preferably, an implementation that is easy to implement without having to maintain birth and death trajectories is used, but any other pitch or noise detector may also be used.

[0094] The IGF module calculates the similarity between the source region and the target region. The target region will be represented by the spectrum from the source region. The cross-correlation method is used to measure the similarity between the source region and the target region. The target region is divided into nTar non-overlapping frequency tiles. For each tile in the target region, nSrc source tiles are created from a fixed starting frequency. These source tiles overlap with a factor between 0 and 1, where 0 represents 0% overlap and 1 represents 100% overlap. Each of these source tiles is associated with the target tile at various lags to find the source tile that best matches the target tile. The best matching tile number is stored in tileNum[idx_tar], the lag most relevant to the target at it is stored in xcorr_lag[idx_tar][idx_src], and the relevant sign is stored in xcorr_sign[idx_tar][idx_src]. In the case of high negative correlation, the source tile needs to be multiplied by -1 before the tile filling process is performed at the decoder. Since pitch masking is used to preserve the tonal components, the IGF module also takes care not to overwrite the tonal components in the spectrum. The band energy parameters are used to store the energy of the target region, which enables accurate reconstruction of the spectrum.

[0095] The reason why this method has certain advantages over classical SBR [1] is that the harmonic grid of the multi-tone signal is preserved by the core encoder, while only the gaps between the sinusoids are filled with the best matching "shaped noise" from the source area. Another advantage of this system over ASR (Exact Spectral Replacement) [2-4] is the absence of signal synthesis segments that create important parts of the signal at the decoder. Instead, this task is taken over by the core encoder, making it possible to preserve important components of the spectrum. Another advantage of the proposed system is the continuous scalability provided by the features. For each tile, only tileNum[idx_tar] and xcorr_lag=0 are used, which is called coarse-grained matching and can be used for low bit rates when the variable xcorr_lag is used for each tile, enabling better matching of the target spectrum and the source spectrum.

[0096] Additionally, a tile selection stabilization technique is proposed, which removes frequency domain artifacts such as warble noise or musical noise.

[0097] In the case of stereo channel pairs, additional joint stereo processing is applied. This is necessary because for a certain target range, the signal can come from highly correlated panned sound sources. In the case where the source regions selected for this specific area are not well correlated, although the energy is matched for the target area, the spatial image may be impaired due to the unrelated source regions. The encoder analyzes each target area energy band, usually performing a cross-correlation of the spectral values, and if a certain threshold is exceeded, a joint label is set for the energy band. In the decoder, if the joint stereo label is not set, the left channel energy band and the right channel energy band are processed separately. In the case of setting the joint stereo label, both energy and patching are performed in the joint stereo domain. The joint stereo information of the IGF area is signaled similarly to the joint stereo information of the core coding, including a label indicating whether the direction of the prediction is from downmix to residual or from residual to downmix in the case of prediction.

[0098] The energy can be calculated based on the transmitted energy in the L / R domain.

[0099] midNrg[k]=leftNrg[k]+rightNrg[k];

[0100] sideNrg[k]=leftNrg[k]-rightNrg[k];

[0101] where k is the frequency index in the transform domain.

[0102] Another solution is to directly compute and send the energy in the joint-stereo domain for the frequency bands where joint-stereo is active, so no additional energy transformation is needed on the decoder side.

[0103] Source tiles are always created from a mid / side matrix:

[0104] midTile[k]=0.5·(leftTile[k]+rightTile[k])

[0105] sideTile[k]=0.5·(leftTile[k]-rightTile[k])

[0106] Energy Adjustment:

[0107] midTile[k]=midTile[k]*midNrg[k];

[0108] sideTile[k]=sideTile[k]*sideNrg[k];

[0109] Joint Stereo->LR Transform:

[0110] If no additional parameters are encoded:

[0111] leftTile[k]=midTile[k]+sideTile[k]

[0112] rightTile[k]=midTile[k]-sideTile[k]

[0113] If additional prediction parameters are encoded and if the signaled direction is from center to side:

[0114] sideTile[k]=sideTile[k]-predictionCoeff·midTile[k]

[0115] leftTile[k]=midTile[k]+sideTile[k]

[0116] rightTile[k]=midTile[k]-sideTile[k]

[0117] If the signaling direction is from side to center:

[0118] midTile1[k]=midTile[k]-predictionCoeff·sideTile[k]

[0119] leftTile[k]=midTile1[k]-sideTile[k]

[0120] rightTile[k]=midTile1[k]+sideTile[k]

[0121] This process ensures that even if the source regions are uncorrelated, the resulting left and right channels still represent correlated and panned sound sources, preserving the stereo image of such regions, based on the tiles used to regenerate highly correlated destination regions and panned destination regions.

[0122] In other words, in the bitstream, a joint stereo tag is transmitted indicating whether L / R or M / S should be used as an example of general joint stereo encoding. In the decoder, first, the core signal is decoded as indicated by the joint stereo tag of the core band. Second, the core signal is stored in L / R and M / S representations. For IGF tile filling, the source tile representation is selected to match the target tile representation as indicated by the joint stereo information of the IGF band.

[0123] Temporal noise shaping (TNS) is a standard technique and is part of ACC [11-13]. TNS can be considered as an extension of the basic scheme of the perceptual encoder, inserting an optional processing step between the filter bank and the quantization stage. The main task of the TNS module is to hide the generated quantization noise in the temporal masking region of the transient-like signal, resulting in a more efficient coding scheme. First, TNS calculates a set of prediction coefficients using "forward prediction" in the transform domain, such as MDCT. These coefficients are then used to flatten the temporal envelope of the signal. When quantization affects the spectrum filtered by TNS, the quantization noise is also flat in time. By applying inverse TNS filtering on the decoder side, the quantization noise is shaped according to the temporal envelope of the TNS filter, so the quantization noise is temporarily masked.

[0124] IGF is based on MDCT representation. For efficient coding, preferably, long blocks of about 20ms must be used. If the signal within such a long block includes transient signals, audible pre-echoes and post-echoes appear in the IGF spectral band due to tile filling.

[0125] In the context of IGF, this pre-echo effect is reduced by using TNS. Here, TNS is used as a Time Tile Shaping (TTS) tool when spectral regeneration is performed on the TNS residual signal in the decoder. The required TTS prediction coefficients are calculated and applied as usual using the full spectrum on the encoder side. The TNS / TTS start and end frequencies are not affected by the IGF start frequency f of the IGF tool. IGFstart Compared with the traditional TNS, the TTS termination frequency is increased to the termination frequency of the IGF tool, which is higher than f IGFstart On the decoder side, the TNS / TTS coefficients are again applied to the full spectrum, i.e. the core spectrum plus the regenerated spectrum plus the tonal components from the pitch map. The application of TTS is necessary to form the time envelope of the regenerated spectrum to match the envelope of the original signal again. Therefore, the pre-echo shown is reduced. In addition, TNS is still used as usual for the signal below f IGFstart The quantization noise is shaped.

[0126] In conventional decoders, spectral patching of an audio signal destroys spectral correlations at patch boundaries and thus impairs the temporal envelope of the audio signal by introducing dispersion. Therefore, another benefit of performing IGF tile filling on the residual signal is that after applying the shaping filter, the tile boundaries are seamlessly correlated, resulting in a more realistic time domain reproduction of the signal.

[0127] In the encoder of the present invention, the spectrum that has undergone TNS / TTS filtering, tone masking processing and IGF parameter estimation lacks any signal above the IGF starting frequency except the tone component. This sparse spectrum is now encoded by the core encoder using the principles of arithmetic coding and predictive coding. These encoded components form the bit stream of audio together with the signaling bits.

[0128] Figure 2A The corresponding decoder implementation is shown. Figure 2A The bit stream corresponding to the encoded audio signal in is input to the demultiplexer / decoder, which is relatively Figure 1B will be connected to blocks 112 and 114. The bitstream demultiplexer separates the incoming audio signal into Figure 1B The first encoding represents 107 and Figure 1B The first coded representation of the first set of first spectral portions is input to the Figure 1B The second coded representation is input to the joint channel decoding block 204 corresponding to the spectral domain decoder 112 of Figure 2A The parameterized decoder 114 shown in FIG. 1 is then input to the Figure 1B The IGF block 202 corresponding to the frequency regenerator 116 of the frequency regenerator 116. The first set of first spectral parts required for frequency regeneration is input to the IGF block 202 via line 203. In addition, after the joint channel decoding 204, a specific core decoding is applied in the tone masking block 206 so that the output of the tone masking 206 corresponds to the output of the spectrum domain decoder 112. Then, the combination is performed by the combiner 208, that is, the frame construction in which the output of the combiner 208 now has a full range spectrum but is still in the TNS / TTS filter domain. Then, in block 210, the inverse TNS / TTS operation is performed using the TNS / TTS filter information provided via line 109, that is, the TTS side information is preferably included in the first encoded representation generated by the spectrum domain encoder 106, or can be included in the second encoded representation, the spectrum domain encoder 106 can be, for example, a simple AAC or USAC core encoder. At the output of block 210, the complete spectrum up to the maximum frequency is provided, which is the full range of frequencies defined by the sampling rate of the original input signal. Then, a spectrum / time conversion is performed in the synthesis filter bank 212 to finally obtain an audio output signal.

[0129] Figure 3A A schematic representation of the spectrum is shown. The spectrum is subdivided into scale factor bands SCB, where Figure 3A In the example shown, there are seven scale factor bands SCB1 to SCB7. Figure 3A As schematically shown in , the scale factor bands may be AAC scale factor bands defined in the AAC standard and have an increasing bandwidth to the upper frequency. It is preferred not to perform smart gap filling from the beginning of the spectrum, i.e. at low frequencies, but to start the IGF operation at the IGF start frequency shown at 309. Thus, the core band extends from the lowest frequency to the IGF start frequency. Above the IGF start frequency, spectral analysis is applied to separate the high resolution spectral components 304, 305, 306, 307 (the first group of first spectral portions) from the low resolution components represented by the second group of second spectral portions. Figure 3A The spectrum that is exemplarily input to the spectral domain encoder 106 or the joint channel encoder 228 is shown, i.e., the core encoder operates at the full range, but encodes a large number of zero spectral values, i.e., these zero spectral values ​​are quantized to zero or set to zero before or after quantization. In any case, the core decoder operates at the full range, i.e., as the spectrum would be as shown, i.e., the core decoder does not have to be aware of any intelligent gap filling or encoding of the second set of second spectral portions with lower spectral resolution.

[0130] Preferably, the high resolution is defined by a linear coding of spectral lines, such as MDCT lines, and the second or low resolution is defined by, for example, calculating only a single spectral value per scale factor band, wherein the scale factor band covers several frequency lines. Thus, the second low resolution is much lower with respect to its spectral resolution than the first or high resolution, which is defined by a linear coding typically applied by a core encoder, such as an AAC or USAC core encoder.

[0131] Regarding the scaling factor or energy calculation, Figure 3B Due to the fact that the encoder is a core encoder and due to the fact that in each frequency band there can be, but not necessarily, a first set of spectrum portions, the core encoder operates not only in the core range below the IGF start frequency 309 but also above the IGF start frequency up to a maximum frequency f IGFstop Calculate the scaling factor for each frequency band within the range of IGFstop Less than or equal to half of the sampling frequency, i.e. f s / 2 .thereby, Figure 3AThe coded tone parts 302, 304, 305, 306, 307 and in this embodiment together with the scale factors SCB1 to SCB7 correspond to high resolution spectrum data. The low resolution spectrum data is calculated starting from the IGF start frequency and corresponds to energy information values ​​E1, E2, E3, E4, which are sent together with the scale factors SF4 to SF7.

[0132] In particular, when the core encoder is in low bit rate conditions, an additional noise filling operation can be additionally applied in the core band, i.e. at frequencies below the IGF start frequency, i.e. in the scale factor bands SCB1 to SCB3. In the noise filling, there are several adjacent spectral lines that are quantized to zero. On the decoder side, these quantized to zero spectral values ​​are resynthesized and the amplitude of the resynthesized spectral values ​​is calculated using the noise filling energy as Figure 3B NF2 shown at 308 in is adjusted. The noise filling energy, which can be given in absolute or relative values, in particular with respect to the scaling factor in USAC, corresponds to the energy of the set of spectral values ​​quantized to zero. These noise filled spectral lines can also be regarded as a third set of third spectral portions, which are generated by a simple noise filling synthesis without any IGF operation relying on frequency regeneration using frequency tiles from other frequencies, and the noise filling synthesis is used to reconstruct the frequency tiles using spectral values ​​from the source range and the energy information E1, E2, E3, E4.

[0133] Preferably, the bands in which the energy information is calculated coincide with the scale factor bands. In other embodiments, energy information value grouping is applied so that, for example, only a single energy information value is sent for scale factor bands 4 and 5, but even in this embodiment, the boundaries of the grouped reconstructed bands coincide with the boundaries of the scale factor boundaries. If a different band separation is applied, some recalculation or synthesis may be applied and this may make sense depending on the implementation.

[0134] Preferably, Figure 1A The spectral domain encoder 106 is as follows Figure 4A Typically, as shown in the MPEG2 / 4AAC standard or the MPEG1 / 2, layer 3 standard, the spectral range ( Figure 4A401 in the MPEG AAC standard) after which the encoded audio signal is forwarded to a scale factor calculator 400. The scale factor calculator is controlled by a psychoacoustic model, which additionally receives the audio signal to be quantized or, as in MPEG1 / 2 layer 3 or in accordance with the MPEG AAC standard, receives a complex spectral representation of the audio signal. The psychoacoustic model calculates a scale factor for representing a psychoacoustic threshold for each scale factor band. In addition, the scale factor is then adjusted so that certain bit rate conditions are achieved by the cooperation of known inner and outer iterative loops or by any other suitable encoding process. The spectral values ​​to be quantized on the one hand and the calculated scale factors on the other hand are input to a quantizer processor 404. In a simple audio encoder operation, the spectral values ​​to be quantized are weighted by the scale factors, and the weighted spectral values ​​are then input to a fixed quantizer, which typically has a compression function up to an amplitude range. Then, at the output of the quantizer processor, there are quantization indices, which are then forwarded to an entropy encoder, which typically has a specific and very efficient encoding for a set of zero quantization indices for "runs" of adjacent frequency values, or also referred to in the art as zero values.

[0135] However, in Figure 1A In an audio encoder of the type described herein, the quantizer processor typically receives information about the second spectral portion from the spectrum analyzer. Thus, the quantizer processor 404 makes sure that the second spectral portion, as identified by the spectrum analyzer 102, in the output of the quantizer processor 404 is zero or has a representation that is recognized by the encoder or decoder as a zero representation, which can be encoded very efficiently, especially when there are "runs" of zero values ​​in the spectrum.

[0136] Figure 4B The implementation of the quantizer processor is shown. The MDCT spectrum value can be input to the set to zero block 410. Then, before weighting is performed by the scale factor in block 412, the second spectrum part has been set to zero. In another implementation, block 410 is not provided, but the set to zero collaboration is performed in block 418 after the weighting block 412. In another implementation, the set to zero operation can also be performed in the set to zero block 422 after the quantization in the quantizer block 420. In this implementation, blocks 410 and 418 will not appear. Generally, at least one of blocks 410, 418, 422 is provided according to the specific implementation.

[0137] Then, at the output of block 422, the Figure 3A Then, the quantized spectrum is input to an entropy encoder such as Figure 2B 232 in which may be a Huffman encoder or an arithmetic encoder as defined in, for example, the USAC standard.

[0138] The zero blocks 410, 418, 422, which are arranged alternately or in parallel with each other, are controlled by a spectrum analyzer 424. Preferably, the spectrum analyzer comprises any implementation of a known tone detector or comprises any different type of detector operatively used to separate the spectrum into components to be encoded at a high resolution and components to be encoded at a low resolution. Other such algorithms implemented in the spectrum analyzer may be a voice activity detector, a noise detector, a speech detector or any other detector that makes decisions based on spectral information of different spectral parts or associated metadata about the resolution requirements.

[0139] Figure 5A Shows Figure 1A The preferred implementation of the time spectrum converter of 506, for example, realizes according to AAC or USAC. Time spectrum converter 100 comprises a window adder 502 controlled by a transient detector 504. When the transient detector 504 detects the transient signal, the switching from the long window to the short window is sent to the window adder by a signal. Then, the window adder 502 is for the frame of overlapping block calculation windowing, and wherein the frame of each windowing has 2N values ​​such as 2048 values ​​usually. Then, in block converter 506, conversion is performed, and this block converter usually provides extraction in addition to make the extraction / conversion of performing combination to obtain the spectrum frame with N values ​​such as MDCT spectrum value. Thereby, for long window operation, the frame at the input end of block 506 comprises 2N values ​​such as 2048 values ​​and spectrum frame then has 1024 values. Then, however, when 8 short blocks are performed, and each short block has 1 / 8 of the windowed time domain value compared to the long window and each spectral block has 1 / 8 of the spectral value compared to the long block, switching is performed on the short blocks. Thus, when this decimation is combined with the 50% overlap operation of the window adder, the spectrum is a critically sampled version of the time domain audio signal 99.

[0140] Then, refer to Figure 5B , Figure 5B Shows Figure 1B The frequency regenerator 116 and the spectrum time converter 118 or Figure 2A The specific implementation of the combined operation of blocks 208 and 212. Figure 5B In the example, we consider a specific reconstruction band such as Figure 3A The scale factor band is 6. The first spectral portion in the reconstructed band is Figure 3A The first spectrum portion 306 of the scale factor band 6 is input to the frame builder / adjuster block 510. In addition, the reconstructed second spectrum portion of the scale factor band 6 is also input to the frame builder / adjuster 510. In addition, the energy information of the scale factor band 6 is as follows: Figure 3BE3 is also input to block 510. The reconstructed second spectral portion in the reconstructed band has been generated by frequency tiling using the source range, and the reconstructed band then corresponds to the target range. Now, energy adjustment of the frame is performed so as to finally obtain a completely reconstructed frame with N values ​​as in e.g. Figure 2A The MDCT is obtained at the output of the combiner 208. Then, in block 512, an inverse block transform / interpolation is performed to obtain 248 time domain values ​​of, for example, 124 spectral values ​​at the input of block 512. Then, a synthetic windowing operation is performed in block 514, which is again controlled by the long window / short window representation sent as side information in the encoded audio signal. Then, in block 516, an overlap / addition operation with the previous time frame is performed. Preferably, the MDCT applies a 50% overlap so that for each new time frame of 2N values, N time domain values ​​are finally output. A 50% overlap is strongly preferred due to the fact that it provides critical sampling and continuous crossing from one frame to the next due to the overlap / addition operation in block 516.

[0141] like Figure 3A As shown in 301, for example, for Figure 3A The envisioned reconstructed frequency band consistent with the scale factor band 6 can additionally apply a noise filling operation not only below the IGF start frequency but also above the IGF start frequency, and then the noise filled spectrum value can also be input to the frame builder / adjuster 510, and adjustment of the noise filled spectrum value can also be applied in this block, or the noise filling energy can be used to adjust the noise filled spectrum value before being input to the frame builder / adjuster 510.

[0142] Preferably, the IGF operation, i.e., the spectrum tiling operation using spectrum values ​​from other parts, can be applied to the complete spectrum. Thus, the spectrum tiling operation can be applied not only in the high frequency band above the IGF start frequency, but also in the low frequency band. In addition, noise filling without spectrum tiling can also be applied not only below the IGF start frequency, but also above the IGF start frequency. However, it has been found that if Figure 3A As shown in , high quality and efficient audio coding can be obtained when the noise filling operation is limited to the spectrum range below the IGF start frequency and when the frequency tile filling operation is limited to the spectrum range above the IGF start frequency.

[0143] Preferably, the target tile (TT) (having a frequency greater than the IGF start frequency) is subject to the scale factor band boundaries of the full rate encoder. The source tile (ST) from which information is obtained, that is, the source tile with a frequency lower than the IGF start frequency is not subject to the scale factor band boundaries. The size of the ST should correspond to the size of the associated TT. This is illustrated using the following example. TT[0] has a length of 10 MDCT frequency points (bins). This corresponds exactly to the length of two subsequent SCBs (such as 4+6). Then, all possible STs to be associated with TT[0] also have a length of 10 frequency points. The second target tile TT[1] adjacent to TT[0] has a length of 15 frequency points I (SCB with a length of 7+8). Then, its ST has a length of 15 frequency points instead of the length of 10 frequency points of TT[0].

[0144] In case a situation occurs where no TT can be found for an ST with the length of the target tile (when, for example, the length of the TT is larger than the available source range), the correlation is not calculated and the source range is copied multiple times into the TT (one after the other so that the frequency line of the lowest frequency of the second copy closely follows in frequency the frequency line of the highest frequency of the first copy) until the target tile TT is completely filled.

[0145] Then, refer to Figure 5C , Figure 5C Shows Figure 1B The frequency regenerator 116 or Figure 2A Block 522 is a frequency tile generator that receives not only the target band ID but also the source band ID. Exemplarily, it is determined on the encoder side: Figure 3A The scale factor band 3 of the source frequency band 7 is very suitable for reconstruction scale factor band 7. Thus, the source frequency band ID will be 2 and the target frequency band ID will be 7. Based on this information, the frequency tile regenerator 522 applies a replication or harmonic tile filling operation or any other tile filling operation to generate the original second portion of spectral components 523. The original second portion of spectral components has the same spectral resolution as the frequency resolution included in the first set of first spectral portions.

[0146] Then, the reconstructed frequency band is Figure 3AThe first spectral portion of 307 of is input to the frame builder 524 and the original second portion 523 is also input to the frame builder 524. Then, the adjuster 526 adjusts the reconstructed frame using the gain factor of the reconstructed band calculated by the gain factor calculator 528. However, importantly, the first spectral portion in the frame is not affected by the adjuster 526, but only the original second portion of the reconstructed frame is affected by the adjuster 526. To this end, the gain factor calculator 528 analyzes the source band or the original second portion 523 and additionally analyzes the first spectral portion in the reconstructed band to finally find the correct gain factor 527 so that the energy of the adjusted frame output by the adjuster 526 has an energy E4 when the scale factor band 7 is assumed.

[0147] In this context, it is very important to evaluate the high frequency reconstruction accuracy of the present invention compared to HE-AAC. Figure 3A 13A . Assume that a prior art encoder, such as the encoder shown in FIG. 13A , detects a portion of the spectrum 307 to be encoded at high resolution as a "missing harmonic". The energy of this spectral component is then sent to the decoder together with the spectral envelope information about the reconstruction band, such as scale factor band 7. The decoder will then reconstruct the missing harmonics. However, the spectral values ​​at which the missing harmonics 307 are reconstructed by the prior art decoder of FIG. 13B will be located in the middle of band 7 at the frequency represented by the reconstruction frequency 390. Thus, the present invention avoids the frequency error 391 that would be introduced by the prior art decoder of FIG. 13B .

[0148] In one implementation, the spectrum analyzer is further implemented to calculate the similarity between the first spectrum portion and the second spectrum portion and determine, for the second spectrum portion within the reconstruction range, the first spectrum portion that matches the second spectrum portion as closely as possible based on the calculated similarity. Then, in this variable source range / destination range implementation, the parameterized encoder will additionally introduce matching information for each destination range representation matching the source range into the second encoded representation. Then, on the decoder side, this information will be provided by Figure 5C The spectrum tile generator 522 uses, Figure 5C The generation of the original second part 523 based on the source band ID and the target band ID is shown.

[0149] In addition, if Figure 3A As shown in , the spectrum analyzer is configured to analyze the spectral representation up to a maximum analysis frequency, which is only a small amount lower than half the sampling frequency, and preferably at least one quarter of the sampling frequency or typically higher.

[0150] As shown, the encoder operates without downsampling and the decoder operates without upsampling.In other words, the spectral domain audio encoder is configured to generate a spectral representation having a Nyquist frequency defined by the sampling rate of the original input audio signal.

[0151] In addition, if Figure 3A As shown in , the spectrum analyzer is configured to analyze a spectrum representation starting from a gap filling start frequency and ending at a maximum frequency represented by a maximum frequency included in the spectrum representation, wherein a spectrum portion extending from the minimum frequency upward to the gap filling start frequency belongs to a first group of spectrum portions, and wherein additional spectrum portions such as 304, 305, 306, 307 having frequency values ​​higher than the gap filling frequency are additionally included in the first group of first spectrum portions.

[0152] As outlined, the spectral domain audio decoder 112 is configured such that the maximum frequency represented by the spectral value in the first decoded representation is equal to the maximum frequency included in the time representation having the sampling rate, wherein the spectral value of the maximum frequency in the first set of first spectral portions is zero or non-zero. In any case, for this maximum frequency in the first set of spectral components, there is a scale factor for the scale factor band, regardless of whether as in Figure 3A and Figure 3B The scaling factor is generated and sent regardless of whether all spectral values ​​in the scaling factor band discussed in the context of FIG. 1 are set to zero or not.

[0153] Therefore, the invention is advantageous in that it enables accurate frequency reproduction of tonal components relative to other parameterization techniques for increasing compression efficiency, such as noise substitution and noise filling, which are specifically designed for efficient representation of noise-like local signal content. Currently, there is no prior art that addresses efficient parameterization of arbitrary signal content by spectral gap filling without being restricted to a fixed a priori partition in a low frequency band (LF) and a high frequency band (HF).

[0154] Embodiments of the inventive system improve upon prior art approaches, providing high compression efficiency, no or only a small amount of perceived annoyance, and full audio bandwidth even at low bit rates.

[0155] The general system includes:

[0156] Full-band core encoding

[0157] Intelligent gap filling (tile filling or noise filling)

[0158] Sparse tonal parts in the core selected by pitch masking

[0159] Full-band joint stereo pair encoding, including tile padding

[0160] TNS for paving

[0161] Spectral whitening within the IGF range

[0162] The first step towards a more efficient system is to remove the need to transform the spectral data into a second transform domain that is different from the transform domain of the core encoding. As most audio codecs such as AAC use MDCT as the basic transform, it is useful to also perform BWE in the MDCT domain. The second requirement of a BWE system would be the need to preserve the pitch grid, whereby even HF tonal components are preserved, so that the quality of the encoded audio is better than existing systems. In order to carefully handle the two requirements mentioned above for the BWE scheme, a new system called Intelligent Gap Filling (IGF) is proposed. Figure 2B shows a block diagram of the proposed system on the encoder side, Figure 2A The system on the decoder side is shown.

[0163] Fig.9A A device for decoding an encoded audio signal comprising an encoded representation of a first set of first spectral portions and an encoded representation of parametric data representing spectral energy of a second set of second spectral portions is shown. Fig.9A In the figure, the first group of first spectrum parts is represented at 901a, and at Fig.9A 901b of represents the coded representation of parameterized data. An audio decoder 900 is provided for decoding the coded representation 901a of the first group of first spectrum parts to obtain a decoded first group of first spectrum parts 904, and for decoding the coded representation of the parameterized data to obtain decoded parameterized data 902 of a second group of second spectrum parts representing the respective energies of the respective reconstructed frequency bands, wherein the second spectrum parts are located in the reconstructed frequency bands. In addition, a frequency regenerator 906 is provided for reconstructing the spectrum values ​​of the reconstructed frequency band including the second spectrum parts. The frequency regenerator 906 uses the first spectrum parts in the first group of first spectrum parts and the respective energy information of the reconstructed frequency band, wherein the reconstructed frequency band includes the first spectrum parts and the second spectrum parts. The frequency regenerator 906 includes a calculator 912, which is used to determine the residual energy information of the cumulative energy of the first spectrum parts including the frequencies in the reconstructed frequency bands. In addition, the frequency regenerator 906 includes a calculator 918, which is used to determine tile energy information of another spectral portion of the reconstructed frequency band, and the frequency values ​​are different from the first spectral portion, wherein these frequency values ​​have frequencies in the reconstructed frequency band, wherein the other spectral portion is to be generated by frequency regeneration using a first spectral portion different from the first spectral portion in the reconstructed frequency band.

[0164] The frequency regenerator 906 also includes a calculator 914 for the missing energy in the reconstructed frequency band, and the calculator 914 operates using the individual energies of the reconstructed frequency band and the residual energy generated by the block 912. In addition, the frequency regenerator 906 includes a spectrum envelope adjuster 916, which adjusts the additional spectrum portions in the reconstructed frequency band based on the missing energy information and the tile energy information generated by the block 918.

[0165] Reference Fig. 9C , Fig. 9C A certain reconstructed frequency band 920 is shown. The reconstructed frequency band comprises a first spectral portion in the reconstructed frequency band schematically shown at 921, such as Figure 3A In addition, the remaining spectral values ​​in the reconstructed frequency band 920 are to be obtained using, for example, Figure 3A The frequency regenerator 906 is configured to generate the original spectrum values ​​of the second spectrum parts 922 and 923. Then, as Fig. 9C As shown in , the gain factor g is calculated to finally adjust the original spectrum values ​​in the frequency bands 922, 923 to obtain a reconstructed and adjusted second spectrum portion in the reconstruction band 920, which now has the same spectrum resolution, i.e., the same line distance, as the first spectrum portion 921. It is important to understand that Fig. 9C The first spectral portion in the reconstructed frequency band shown at 921 in FIG. 1 is decoded by the audio decoder 900 without being affected by Fig. 9B The envelope adjustment of the execution block 916 is affected. Alternatively, the first spectral portion in the reconstructed frequency band represented at 921 is left as is, since the first spectral portion is output by the full bandwidth or full rate audio decoder 900 via line 904.

[0166] Subsequently, a specific example using real numbers is discussed. The remaining residual energy calculated by block 912 is, for example, 5 energy units, and this energy is the energy of the exemplarily represented 4 spectral lines in the first spectral portion 921 .

[0167] In addition, Figure 3B or Figure 3AThe energy value E3 of the reconstructed band corresponding to the scale factor band 6 of is equal to 10 units. Importantly, the energy value includes not only the energy of the spectral parts 922, 923, but the entire energy of the reconstructed band 920 calculated on the encoder side, i.e., before performing the spectral analysis using, for example, channel masking. Thus, 10 energy units cover the first spectral part and the second spectral part in the reconstructed band. Then, it is assumed that the energy of the source range data of blocks 922, 923 or the original target range data of blocks 922, 923 is equal to 8 energy units. Thus, 5 units of lost energy are calculated.

[0168] Based on the lost energy divided by the tile energy tEk, a gain factor of 0.79 is calculated. Then, the original spectral lines of the second spectral parts 922, 923 are multiplied by the calculated gain factor. Thus, only the spectral values ​​of the second spectral parts 922, 923 are adjusted, while the spectral lines of the first spectral part 921 are not affected by the envelope adjustment. After multiplying the original spectral values ​​of the second spectral parts 922, 923, a complete reconstructed frequency band is calculated, which includes the first spectral part in the reconstructed frequency band and includes the spectral lines in the second spectral parts 922, 923 in the reconstructed frequency band 920.

[0169] Preferably, the source range used to generate the original spectral data in the frequency bands 922 , 923 is below the IGF start frequency 309 with respect to frequency, while the reconstruction frequency band 920 is above the IGF start frequency 309 .

[0170] Furthermore, preferably, the reconstruction band boundaries coincide with the scale factor boundaries. Thus, in one embodiment, the reconstruction bands have the size of the corresponding scale factor bands of the core audio decoder, or are sized such that, when energy pairing is applied, the energy value of the reconstruction band provides the energy of an integer number of scale factor bands equal to or greater than 2. Thus, when it is assumed that energy accumulation is performed for scale factor band 4, scale factor band 5, and scale factor band 6, then the lower frequency boundary of reconstruction band 920 is equal to the lower boundary of scale factor band 4, and the upper frequency boundary of reconstruction band 920 coincides with the upper boundary of scale factor band 6.

[0171] Then, discuss Fig.9D To show Fig.9A The audio decoder 900 receives dequantized spectral values ​​corresponding to a first spectral portion of a first set of spectral portions and, in addition, converts the dequantized spectral values ​​into Figure 3B The scale factors of the scale factor bands shown in FIG. 1 are provided to the inverse scaling block 940. The inverse scaling block 940 provides Figure 3A All first groups of first spectrum parts of the IGF start frequency 309 and additionally provide first spectrum parts above the IGF start frequency, i.e., are located at Fig.9DThe reconstructed frequency band shown at 941 in Figure 3A In addition, the first spectral portion in the source band for frequency tiling filling in the reconstruction band is provided to the envelope adjuster / calculator 942, and the block additionally receives the envelope adjuster / calculator 942 which is set relative to the envelope adjuster / calculator 942. Fig.9D The energy information of the reconstructed frequency band of the parameterized side information of the encoded audio signal shown at 943 in FIG. Then, the envelope adjuster / calculator 942 provides Fig. 9B and Fig. 9C The function of , and finally outputs the adjusted spectrum value of the second spectrum part in the reconstructed frequency band. These adjusted spectrum values ​​922, 923 and Fig.9D The first spectral portion 921 in the reconstructed frequency band represented by the line 941 in jointly represents the complete spectral representation of the reconstructed frequency band.

[0172] Then, refer to Fig. 10A and Fig. 10B , Fig. 10A and Fig. 10B A preferred embodiment of an audio encoder for encoding an audio signal to provide or generate an encoded audio signal is described. The encoder comprises a time / spectral converter 1002, which feeds a spectrum analyzer 1004, and the spectrum analyzer 1004 is connected to a parameter calculator 1006 on the one hand and to an audio encoder 1008 on the other hand. The audio encoder 1008 provides an encoded representation of a first group of first spectral portions and does not cover a second group of second spectral portions. On the other hand, the parameter calculator 1006 provides energy information of reconstructed frequency bands covering the first spectral portions and the second spectral portions. In addition, the audio encoder 1008 is configured to generate a first encoded representation of a first group of first spectral portions with a first spectral resolution, wherein the audio encoder 1008 provides scale factors for all frequency bands of the spectral representation generated by block 1002. In addition, as Figure 3B As shown in , the encoder provides a Figure 3A Energy information of at least the reconstructed frequency band above the shown IGF start frequency 309. Thus, for a reconstructed frequency band preferably coinciding with a scale factor band or with a group of scale factor bands, two values ​​are given, namely the corresponding scale factor from the audio encoder 1008 and the energy information additionally output by the parameter calculator 1006.

[0173] Preferably, the audio encoder has scale factor bands with different frequency bandwidths, i.e. with different numbers of spectral values. Therefore, the parameterization calculator comprises a normalizer 1012 for normalizing the energies of the different bandwidths relative to the bandwidth of a particular reconstruction band. To this end, the normalizer 1012 receives as input the energy in the band and a number of spectral values ​​in the band, and then the normalizer 1012 outputs the normalized energy per reconstruction / scale factor band.

[0174] also, Fig. 10A The parameterization calculator 1006A includes an energy value calculator, which is used to Fig. 10A 1007 in FIG. 1004 receives control information from a core or audio encoder 1008. The control information may include information about the long / short blocks used by the audio encoder and / or grouping information. Thus, while the information about the long / short blocks and the grouping information about the short windows relate to "time" grouping, the grouping information may additionally refer to spectral grouping, i.e., grouping two scale factor bands into a single reconstructed band. Thus, when only the spectral portion has been grouped, the energy value calculator 1014 outputs a single energy value for each grouped band covering the first spectral portion and the second spectral portion.

[0175] Fig. 10D Yet another embodiment for implementing spectrum grouping is shown. To this end, block 1016 is configured to calculate energy values ​​for two adjacent frequency bands. Then, in block 1018, the energy values ​​of the two adjacent frequency bands are compared, and when the energy values ​​are not significantly different or differ to a lesser extent than, for example, those defined by a threshold, a single (normalized) value for the two frequency bands is generated as shown in block 1020. As shown by line 1019, block 1018 can be bypassed. In addition, the generation of a single value for two or more frequency bands performed by block 1020 can be controlled by an encoder bit rate controller 1024. Thus, when the bit rate is to be reduced, the encoding bit rate controller 1024 controls block 1020 to generate a single normalized value for two or more frequency bands, even if the comparison in block 1018 is not allowed to group the energy information values.

[0176] In case the audio encoder performs grouping of two or more short windows, this grouping is also applied for the energy information. When the core encoder performs grouping of two or more short blocks, then for these two or more blocks only a single set of scale factors is calculated and sent. Then, on the decoder side, the audio decoder applies the same set of scale factors for both grouped windows.

[0177] Regarding the energy information calculation, the spectrum values ​​in the reconstructed band are accumulated for two or more short windows. In other words, this means that the spectrum values ​​in a certain reconstructed band of a short block and a subsequent short block are accumulated together, and only a single energy information is sent for this reconstructed band covering two short blocks. Then, on the decoder side, the energy information is not performed separately for each short block. 9A to 9D The envelope adjustment discussed above, but for a group of short windows, performs the 9A to 9D Envelope adjustment for discussion.

[0178] Then, the corresponding normalization is applied again so that even if any grouping in frequency or grouping in time has been performed, the normalization easily enables: for the calculation of the energy value information on the decoder side, on the one hand only the energy value information and the amount of spectral lines in the reconstructed frequency band or in a group of grouped reconstructed frequency bands have to be known.

[0179] Furthermore, it is emphasized that information about spectral energy, information about individual energies or individual energy information, information about residual energy or residual energy information, information about tile energy or tile energy information, or information about lost energy or lost energy information may include not only energy values, but also (e.g. absolute) amplitude values, level values ​​or any other values ​​from which the final energy value can be derived. Therefore, the information about energy may, for example, include the energy value itself and / or the value of the level and / or amplitude and / or absolute amplitude.

[0180] Fig. 12A Another implementation of an apparatus for decoding is shown. A bitstream is received by a core decoder 1200, which may be, for example, an AAC decoder. The result is configured to a stage for performing bandwidth extension patching or tiling 1202 corresponding to, for example, the frequency regenerator 604. The process of patch / tiling adaptation and post-processing is then performed, and, when patch adaptation is performed, the frequency regenerator 1202 is controlled to perform another frequency regeneration, but now with, for example, adjusted frequency boundaries. In addition, when patching processing is performed, such as by eliminating or attenuating pitch lines, then the result is forwarded to a block 1206 that performs parameter-driven bandwidth envelope shaping as, for example, also discussed in the context of block 712 or block 826. The result is then forwarded to a synthesis transform block 1208 for performing, for example, to a post-processing step. Fig. 12A The transformation of the final output domain to the PCM output domain is shown.

[0181] The main features of the embodiments of the invention are as follows:

[0182] The preferred embodiment is based on the MDCT which exhibits the warble artifacts cited above if tonal spectral regions are clipped due to inappropriate choice of crossover frequencies and / or patch edges, or if tonal components are placed too close to patch boundaries.

[0183] Fig. 12B It is shown how the newly proposed technique reduces the artifacts found in the prior art BWE methods. Fig. 12B In panel (2) of , a stylized amplitude spectrum of the output of a contemporary BWE method is shown. In this example, the signal is perceptually impaired by the beat caused by two adjacent tones, and is also perceptually impaired by the segmentation of the tones. The two problematic spectral regions are each marked with a circle.

[0184] To overcome these problems, the new technique first detects the spectral position of the tonal components included in the signal. Then, according to one aspect of the invention, it attempts to adjust the transition frequencies between the LF and all patches by individual shifts (within given limits) so that the splitting or beating of the tonal components is minimized. For this purpose, preferably, the transition frequencies must match the local spectral minima. This step is done in Fig. 12B Panels (2) and (3) show that the transition frequency f x2 Moving towards higher frequencies, the result is fˊ x2 .

[0185] According to another aspect of the present invention, if problematic spectral content in the transition region remains, at least one misplaced tonal component is removed to reduce beat artifacts or vibrato at the transition frequency. Fig. 12B As shown in panel (3) of , this is done via spectral extrapolation or interpolation / filtering. Thus, the tonal component is removed from base point to base point, i.e. from its left local minimum to its right local minimum. Fig. 12B Panel (4) shows the resulting spectrum after applying the inventive technique.

[0186] In other words, Fig. 12B The original signal is shown in the upper left corner, panel (1). The comparative bandwidth extended signal with problematic areas indicated by ellipse 1220 and ellipse 1221 is shown in the upper right corner, panel (2). Two preferred patch or frequency tiling processing features are shown in the lower left corner, panel (3). By increasing the frequency boundary fˊ x2 The segmentation of the tonal parts is solved so that there is no longer a clipping of the corresponding tonal parts. Furthermore, a gain function 1030 is applied for eliminating the tonal parts 1031 and 1032, or alternatively, an interpolation is represented as shown by 1033. Finally, Fig. 12B The lower right panel (4) shows the improved signal resulting from the tile / patch frequency adjustment on the one hand and the elimination or at least attenuation of the problematic tonal parts.

[0187] As discussed earlier, Fig. 12BPanel (1) shows the original spectrum, and the original spectrum has a frequency up to the crossover or gap filling start frequency f x1 core frequency range.

[0188] Therefore, the frequency f x1 The boundary frequency 1250 between the source range 1252 and the reconstruction range 1254 is shown. The reconstruction range 1254 has a frequency less than or equal to the Nyquist frequency f at the boundary frequency 1250. Nyquist On the encoder side, it is assumed that the signal is bandwidth limited to f x1 or when the technique for smart gap filling is applied, assuming f x1 and Figure 3A The gap filling start frequency corresponds to 309. Depending on the technology, above f x1 The reconstruction range will be empty (in the case of the implementation of Figures 13A and 13B) or as in Figure 3A The discussion in the context of will include a specific first spectrum portion to be encoded having a high resolution.

[0189] Fig. 12B Panel (2) shows, for example, Fig. 7A 12 is a preliminary regenerated signal generated by block 702 of FIG. 12 with two problematic portions. One problematic portion is shown at 1220. The frequency distance between the tone portion within the core region shown at 1220a and the tone portion at the beginning of the frequency tile shown at 1220b is so small that a beat artifact is created. Another problem is that at the upper boundary of the first frequency tile generated by the first patching operation or frequency tiling operation shown at 1225 is a clipped or split tone portion 1226. When this tone portion 1226 is at the same frequency as the first frequency tile, the frequency artifact is generated. Fig. 12B When compared with other tonal portions in the source range 1252, it becomes clear that this width is smaller than the width of a typical tonal portion and this means that the tonal portion has been split by setting the frequency boundary between the first frequency tile 1225 and the second frequency tile 1227 at the wrong place in the source range 1252. In order to solve this problem, as Fig. 12B As shown in panel (3) in the figure, the boundary frequency f x2 It has been modified to be slightly louder so that clipping of this tonal portion does not occur.

[0190] On the other hand, the changed fˊ x2 This process does not effectively solve the beat problem, which is therefore solved by Fig. 7A The tonal component removal is addressed by filtering or interpolation or any other process discussed in the context of block 708. Therefore, Fig. 12B The sequential application of transition frequency adjustment 706 and removal of tonal components at the boundary shown at 708 is shown.

[0191] Another option would be to set the transition boundary f x1 It is slightly lowered so that the tone portion 1220a is no longer in the core range. Then, the transition frequency f x1 Set at a lower value to remove or eliminate the tonal portion 1220a.

[0192] This process is also performed to resolve the problem of problematic tonal components 1032. By x2 Set higher, the portion of the spectrum in which the tone portion 1032 is located can be regenerated within the first patching operation 1225, so that two adjacent or neighboring tone portions do not appear.

[0193] Basically, the beat problem depends on the amplitude and distance of the frequencies of adjacent tonal components. Preferably, the detectors 704 and 720 or more generally the analyzer 602 are configured in such a way that a pair of frequencies located below, for example, f x1 、f x2 、fˊ x2 The lower spectral part in the frequency of the transition frequency is analyzed to locate any tonal components. In addition, the spectral range above the transition frequency is also analyzed to detect tonal components. When the detection results in two tonal components, one to the left of the transition frequency and one to the right (referenced to the rising frequency) in frequency, then, the activation Fig. 7A . The detection of the tonal components is performed in a specific detection range which extends in both directions by at least 20% of the bandwidth of the corresponding frequency band and preferably only extends up to 10% downwards towards the left of the transition frequency and upwards towards the right of the transition frequency relative to the corresponding bandwidth, i.e. the bandwidth of the source range on the one hand and the bandwidth of the reconstruction range on the other hand, or when the transition frequency is the transition frequency between two frequency tiles 1225 and 1227, by an amount corresponding to 10% of the corresponding frequency tile. In another embodiment, the predetermined detection bandwidth is 1 bark. It should be possible to remove the tonal parts within 1 bark around the patch boundary so that the complete detection range is 2 barks, i.e. 1 bark in the lower frequency band and 1 bark in the higher frequency band, wherein 1 bark in the lower frequency band is immediately adjacent to 1 bark in the higher frequency band.

[0194] According to another aspect of the invention, to reduce filter ringing artifacts, a crossover filter in the frequency domain is applied to two consecutive spectral regions, ie between the core band and the first patch or between two patches. Preferably, the crossover filter is signal adaptive.

[0195] The crossover filter consists of two filters, a fade-out filter h applied to the lower spectral region outand a fade-in filter h applied to higher spectral regions in .

[0196] The length of each filter is N.

[0197] Additionally, the slopes of the two filters are characterized by a signal-adaptive value called Xbias that determines the notch characteristics of the crossover filter, where 0 ≤ Xbias ≤ N:

[0198] If Xbias=0, the sum of the two filters is equal to 1, ie there is no notch filter characteristic in the resulting filter.

[0199] If Xbias = N, then both filters are completely zero.

[0200] The basic design of the crossover filter is governed by the following equation:

[0201]

[0202] h out (k)+h in (k) = 1, Xbias = 0

[0203] Wherein, k=0, 1, ..., N-1 is a frequency index. Fig. 12C An example of such a crossover filter is shown.

[0204] In this example, the following equation is used to create the filter h out :

[0205]

[0206] The following equation describes how to then apply the filter h in and filter h out :

[0207] Y(k t -(N-1)+k)=LF(k t -(N-1)+k)·h out (k)+

[0208] HF(k t -(N-1)+k)·h in (k), k=0, 1, ..., N-1

[0209] Where Y represents the assembled spectrum, k t is the transition frequency, LF is the low frequency content and HF is the high frequency content.

[0210] Next, evidence of the advantages of this technique will be presented. The original signal in the following example is a transient-like signal, specifically a low-pass filtered version thereof with a cut-off frequency of 22kHz. First, the transient signal is band-limited to 6kHz in the transform domain. Subsequently, the bandwidth of the low-pass filtered original signal is extended to 24kHz. The bandwidth extension is accomplished by copying the LF band three times to completely fill the frequency range that is available above 6kHz within the transform.

[0211] Fig.11A The spectrum of this signal is shown, which can be considered as a typical spectrum of filter ringing artifacts spectrally surrounding transient signals due to the above-mentioned brick-wall characteristics of the transition (speech peaks 1100). By applying the inventive method, the filter ringing is reduced by about 20dB at each transition frequency (reducing speech peaks).

[0212] Fig. 11B and Fig. 11C The same effect is shown in a different illustration. Fig. 11B FIG. 6 shows a spectrum diagram of the mentioned transient-like signal with filter ringing artifacts, which precede and follow the transient signal in the time domain after applying the BWE technique described above without any filter ringing suppression. Each horizontal line represents the filter ringing at the transition frequency between consecutive patches. FIG. 7 shows the same signal after applying the inventive method with BWE. By applying ringing suppression, the filter ringing is reduced by about 20 dB compared to the signal shown in the previous figure.

[0213] Then, discuss Fig.14A and Fig. 14B To further illustrate the crossover filter invention aspects that have been discussed in the context of having an analyzer feature. However, it is also possible to independently FIG. 6A to FIG. 7B The crossover filter 710 is implemented in accordance with the present invention discussed in the context of FIG.

[0214] Fig.14A An apparatus for decoding an encoded audio signal comprising an encoded core signal and information about parameterized data is shown. The apparatus comprises a core decoder 1400 for decoding the encoded core signal to obtain a decoded core signal. The decoded core signal may be bandwidth limited in the implementation scenarios of FIGS. 13A and 13B , or the core decoder may be bandwidth limited in the implementation scenarios of FIGS. 1 to 13B . Figure 5C or 9A to 10D In the background would be a full frequency range or full rate encoder.

[0215] Furthermore, a tile generator 1404 is used to generate one or more spectral tiles having frequencies not included in the decoded core signal using the spectral portion of the decoded core signal. The tiles may be the reconstructed second spectral portion within a reconstructed frequency band, which may be, for example, Figure 3A The spectral tiles may comprise a first spectral portion to be reconstructed with high resolution as shown in the context of FIG. 13A , but alternatively the spectral tiles may also comprise completely empty frequency bands when the encoder performs strict frequency band limitation as shown in FIG. 13A .

[0216] In addition, a crossover filter 1406 is provided to perform spectral crossover filtering on the decoded core signal and the first frequency tile whose frequency extends from the gap filling frequency 309 to the first tile stop frequency, or to perform spectral crossover filtering on the first frequency tile 1225 and the second frequency tile 1221. The lower boundary frequency of the second frequency tile is adjacent to the upper boundary frequency of the first frequency tile 1225 in frequency.

[0217] In another implementation, the crossover filter 1406 output signal is fed to an envelope adjuster 1408, which applies the parameterized spectral envelope information included in the encoded audio signal as parameterized side information to ultimately obtain an envelope-adjusted regenerated signal. Figure 1B or Fig. 6A As shown, elements 1404, 1406, and 1408 may be implemented as frequency regenerators.

[0218] Fig. 14B Another implementation of the crossover filter 1406 is shown. The crossover filter 1406 includes a fade-out subfilter receiving a first input signal IN1 and a second fade-in subfilter 1422 receiving a second input IN2, and the results or outputs of the two filters 1420 and 1422 are provided to a combiner 1424, such as an adder. The adder or combiner 1424 outputs the spectrum values ​​of the frequency points. Fig. 12C An example cross-fade function is shown including a fade-out sub-filter characteristic 1420a and a fade-in sub-filter characteristic 1422a. Fig. 12C In the example of , the two filters have a certain frequency overlap equal to 21, ie N = 21. Therefore, for example, other frequency values ​​of the source range 1252 are not affected. Only the highest 21 frequency points of the source range 1252 are affected by the fade-out function 1420a.

[0219] On the other hand, only the lowest 21 frequency lines of the first frequency tile 1225 are affected by the fade-in function 1422a.

[0220] In addition, it is clear from the crossfade function that the frequency lines between 9 and 13 are affected, but the fade-in function does not actually affect the frequency lines between 1 and 9, and the fade-out function 1420a does not affect the frequency lines between 13 and 21. This means that only the overlap between frequency lines 9 and 13 is necessary, and as shown in f x1The crossover frequency would be placed at frequency sample or frequency point 11. Thus, an overlap of only two frequency points or frequency values ​​between the source range and the first frequency tile would be required to implement the crossover or crossfade function.

[0221] Depending on the specific implementation, higher or lower overlap can be applied, and in addition, other gradient functions besides the cosine function can be used. Fig. 12C As shown, preferably, a specific notch in the crossover range is applied. Stated differently, when it is the case in a crossfade function without a notch, the energy in the boundary range will be reduced because the two filter functions are not summed up into one. The energy loss at the boundary of the frequency tile, i.e. the first frequency tile, will be attenuated at the lower boundary and the upper boundary, and the energy will be more concentrated in the middle of the frequency band. However, since the spectral envelope adjustment occurs after processing through the crossover filter, all frequencies are not touched, but are instead represented by spectral envelope data such as Figure 3A In other words, then, Fig. 9B The calculator 918 of will calculate the "generated original target range" as the output of the crossover filter. In addition, the energy loss due to the removal of the tonal part by interpolation can also be compensated by the fact that this removal will in turn result in a lower tile energy, and the gain factor of the complete reconstructed frequency band will become higher. On the other hand, however, the crossover frequency results in a greater concentration of energy in the middle of the frequency tile, and this effectively reduces the energy loss caused in particular by, for example, FIG. 11A to FIG. 11C Artifacts caused by transient signals are discussed in the context of

[0222] Fig. 14B Different input combinations are shown. For filtering at the boundary between the source frequency range and the frequency tile, input 1 is the upper spectral portion of the core range and input 2 is the lower spectral portion of the first frequency tile or a single frequency tile (when only a single frequency tile is present). In addition, the input can be a first frequency tile, and the transition frequency can be the upper frequency boundary of the first tile, and the input to subfilter 1422 would be the lower portion of the second frequency tile. When Fig. 12C When the characteristic is used, when there is an additional third frequency tile, the other transition frequency will be the frequency boundary between the second frequency tile and the third frequency tile, and the input of the fade-out sub-filter 1421 will be the upper frequency spectrum range of the second frequency tile determined by the filter parameters, and the input into the fade-in sub-filter 1422 will be the lower part of the third frequency tile, and Fig. 12C In this example, these are the lowest 21 spectral lines.

[0223] like Fig. 12CAs shown, it is preferred to have the parameter N equal for the fade-out sub-filter and the fade-in sub-filter. However, this is not necessary. The value of N can vary, and then the result will be that the filter "notch" will be asymmetric between the lower range and the upper range. In addition, it is not necessary that the fade-in / fade-out function must be as shown. Fig. 12C Alternatively, it is also possible to use asymmetric characteristics.

[0224] Furthermore, the crossover filter characteristic signal is preferably adaptive. Thus, the filter characteristic is adapted based on the signal analysis. Since the crossover filter is particularly useful for transient signals, it is detected whether a transient signal is present. When a transient signal is present, it is possible to use Fig. 12C However, when a non-transient signal is detected, it is preferred to change the filter characteristics to reduce the effect of the crossover filter. This can be done, for example, by setting N to zero or by setting X bias is set to zero to obtain such that the sum of the two filters is equal to 1, i.e. a non-notch filter characteristic is present in the resulting filter. Alternatively, in the case of non-transient signals, the crossover filter 1406 can simply be bypassed. However, preferably, by varying the parameters N and X bias To change the filter characteristic relatively slowly to avoid the artifacts obtained by changing the filter characteristic quickly. In addition, even if the signal detected by the specific transient signal / tone detector changes more rapidly, the low-pass filter preferably only allows such relatively small filter characteristic changes. Fig.14A The detector is shown at 1405 in FIG. It may receive an input signal into the tile generator or an output signal of the tile generator 1404, or it can even be connected to the core decoder 1400 to obtain transient signal / non-transient signal information, such as short block indication from AAC decoding, for example. Naturally, it is also possible to use the same Fig. 12C The crossover filter shown is different from any other crossover filter.

[0225] Then, based on transient detection or based on tone detection or based on any other signal characteristic detection, the characteristics of the crossover filter 1406 are changed as discussed.

[0226] Although some aspects are described in the context of a device for encoding or decoding, it is clear that these aspects also represent the description of the corresponding method, wherein a block or device corresponds to a method step or the feature of a method step. Similarly, the aspects described in the context of the method step also represent the description of the corresponding block or project or the feature of the corresponding device. Some or all of the method steps can be performed by (or using) hardware devices such as, for example, microprocessors, programmable computers or electronic circuits. In some embodiments, one or more of the most important method steps can be performed by such a device.

[0227] Depending on certain implementation requirements, embodiments of the present invention may be implemented in hardware or software. The implementation may be implemented using a non-transitory storage medium such as a digital storage medium, such as a floppy disk, a hard disk drive (HDD), a DVD, a Blu-ray, a CD, a ROM, a PROM and an EPROM, an EEPROM or a flash memory, on which are stored electrically readable control signals that cooperate (or are capable of cooperating) with a programmable computer system so that the corresponding method is performed. Thus, the digital storage medium may be computer readable.

[0228] Some embodiments according to the invention comprise a data carrier having electronically readable control signals, which are capable of cooperating with a programmable computer system, such that one of the methods described herein is performed.

[0229] Generally, embodiments of the present invention can be implemented as a computer program product with a program code, when the computer program product runs on a computer, the program code is operative for performing one of the methods.The program code may be stored, for example, on a machine readable carrier.

[0230] Other embodiments comprise the computer program for performing one of the methods described herein, stored on a machine readable carrier.

[0231] In other words, an embodiment of the inventive method is, therefore, a computer program having a program code for performing one of the methods described herein, when the computer program runs on a computer.

[0232] A further embodiment of the method of the present invention is therefore a data carrier (or a digital storage medium or a computer-readable medium) comprising, stored thereon, the computer program for performing one of the methods described herein. The data carrier, the digital storage medium or the recorded medium are typically tangible and / or non-transitory.

[0233] A further embodiment of the inventive method is, therefore, a data stream or a sequence of signals representing the computer program for performing one of the methods described herein.The data stream or the sequence of signals may be configured to be transmitted, for example, via a data communication connection, for example via the Internet.

[0234] A further embodiment comprises a processing means, for example a computer or a programmable logic device, configured to or adapted to perform one of the methods described herein.

[0235] A further embodiment comprises a computer having installed thereon the computer program for performing one of the methods described herein.

[0236] According to another embodiment of the present invention, a device or system is configured to transmit (for example, electronically or optically) a computer program for performing one of the methods described herein to a receiver. The receiver may be, for example, a computer, a mobile device, a storage device, etc. The device or system may include, for example, a file server for transmitting the computer program to the receiver.

[0237] In some embodiments, a programmable logic device (e.g., a field programmable gate array) can be used to perform some or all of the functions of the methods described herein. In some embodiments, a field programmable gate array can collaborate with a microprocessor to perform one of the methods described herein. Typically, preferably, these methods are performed by any hardware device.

[0238] The above embodiments are merely illustrative of the principles of the present invention. It should be understood that modifications and variations of the arrangements and details described herein will be apparent to other persons skilled in the art. Therefore, it is intended that the present invention be limited only by the scope of the appended patent claims and not by the specific details given by way of the description and illustration of the embodiments herein.

[0239] Citation list

[0240] [1] Dietz, L. Liljeryd, K. and O. Kunz, “Spectral Band Replication, a novel approach in audio coding”, 112th AES (Audio Engineering Society) Conference, Munich, May 2002

[0241] [2] Ferreira, D. Sinha, “Accurate Spectral Replacement,” Audio Engineering Society Conference, Barcelona, ​​Spain, 2005

[0242] [3] D. Sinha, A. Ferreira1, and E. Harinarayanan, “A Novel Integrated Audio Bandwidth Extension Toolkit (ABET)”, Audio Engineering Society Conference, Paris, France, 2006

[0243] [4] R. Annadana, E. Harinarayanan, A. Ferreira, and D. Sinha, “New Results in Low Bit Rate Speech Coding and Bandwidth Extension,” Audio Engineering Society Conference, San Francisco, USA, 2006

[0244] [5]T. M.Bartkowiak, “Audio bandwidth extension by frequenciescaling of sinusoidal partials”, Audio Engineering Society Conference, San Francisco, USA, 2008

[0245] [6] J. Herre, D. Schulz, Extending the MPEG-4AAC Codec by Perceptual NoiseSubstitution, 104th AES (Audio Engineering Society) Conference, Amsterdam, 1998, preprint 4720

[0246] [7] M. Neuendorf, M. Multrus, N. Rettelbach et al., MPEG Unified Speech and Audio Coding - The ISO / MPEG Standard for High-Efficiency Audio Coding of all Content Types, 132nd AES (Audio Engineering Society) Conference, Budapest, Hungary, April 2012

[0247] [8] McAulay, Robert J., Quatieri, and Thomas F., “Speech Analysis / Synthesis Based on a Sinusoidal Representation,” IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 34(4), August 1986

[0248] [9] Smith, J. O. and Serra, X., “PARSHL: An analysis / synthesis program for non-harmonic sounds based on a sinusoidal representation”, Proceedings of the International Conference on Computer Music, 1987

[0249]

[10] Purnhagen, H.; Meine, Nikolaus, “HILN - the MPEG-4 parametric audiocoding tools”, Circuits and Systems, Proceedings of the 2000 ISCAS (International Symposium on Circuits and Systems), Geneva, 2000, 2000 IEEE International Symposium, Vol. 3, pp. 201, 204, Vol. 3, 2000

[0250]

[11] International Standard ISO / IEC 13818-3, “Generic Coding of Moving Pictures and Associated Audio: Audio”, Geneva, 1998

[0251]

[12] M. Bosi, K. Brandenburg, S. Quackenbush, L. Fielder, K. Akagiri, H. Fuchs, M. Dietz, J. Herre, G. Davidson, Oikawa, “MPEG-2 Advanced Audio Coding”, 101st AES (Audio Engineering Society) Conference, Los Angeles, 1996

[0252]

[13] J. Herre, “Temporal Noise Shaping, Quantization and Coding methods in Perceptual Audio Coding: A Tutorial introduction”, 17th AES (Audio Engineering Society) International Conference on High-Quality Audio Coding, August 1999

[0253]

[14] J. Herre, “Temporal Noise Shaping, Quantization and Coding methods in Perceptual Audio Coding: A Tutorial introduction”, 17th AES (Audio Engineering Society) International Conference on High-Quality Audio Coding, August 1999

[0254]

[15] International Standard ISO / IEC 23001-3:2010, Unified speech and audio coding Audio, Geneva, 2010

[0255]

[16] International Standard ISO / IEC 14496-3:2005, Information technology-Coding of audio-visual objects-Part 3: Audio, Geneva, 2005

[0256]

[17] P. Ekstrand, “Bandwidth Extension of Audio Signals by Spectral Band Replication,” in Proceedings of the 1st IEEE Benelux Workshop on MPCA, Leuven, November 2002

[0257]

[18] F. Nagel, S. Disch, S. Wilde, A continuous modulated single sideband bandwidth extension, ICASSP International Conference on Acoustics, Speech and Signal Processing, Dallas, Texas (USA), April 2010

[0258]

[19] Liljeryd, Lars; Ekstrand, Per; Henn, Fredrik; Kjorling, Kristofer: Spectral translation / folding in the subband, U.S. Patent 8,412,365, April 2, 2013

[0259]

[20] Daudet, L.; Sandler, M.; “MDCT analysis of sinusoids: exact results and applications to coding artifacts reduction,” Speech and Audio Processing, IEEE Transactions on Speech and Audio Processing, Vol. 12, No. 3, pp. 302–312, May 2004

Claims

1. A device for decoding an encoded audio signal comprising an encoded core signal and parametric data (605), comprising: A core decoder (600) for decoding the encoded core signal to obtain a decoded core signal; an analyzer (720) for analyzing (704) the preliminary regenerated signal (703) to detect a pseudo sound generating signal portion as an analysis result (603); as well as a frequency regenerator (604) for regenerating a portion of the spectrum not included in the decoded core signal using the portion of the spectrum of the decoded core signal, the parameterized data (605) and the analysis result (603), Wherein, the frequency regenerator (604) includes an operator (722), which is used to operate the preliminary regeneration signal (703) or to perform additional regeneration using parameters different from the parameters used to generate the preliminary regeneration signal (703) to reduce or eliminate the artifact generating signal portion in the preliminary regeneration signal (703), wherein the operator (722) is controlled by the analyzer (720).

2. The device according to claim 1, in, The preliminary regenerated signal (703) has a spectral portion not included in the decoded core signal and is generated by obtaining a regenerated spectral portion using a spectral portion of the decoded core signal; and Wherein, the frequency regenerator (604) is configured to: detect (704) the portion of the artifact generating signal near a frequency boundary between the decoded core signal and the regenerated spectrum portion or near a frequency boundary between two regenerated spectrum portions generated by using the same or different spectrum portions of the decoded core signal.

3. The device according to claim 2, in, The frequency regenerator (604) includes a frequency tile generator (820) configured to use one or more spectral portions of the decoded core signal to obtain the spectral portion not included in the decoded core signal to obtain an original spectral portion; wherein the operator is configured to operate the original spectrum portion or the frequency tile generator (820) to obtain an operating spectrum portion; and The frequency regenerator (604) further comprises a spectrum envelope adjuster (826), wherein the spectrum envelope adjuster (826) is configured to: use the parameterized data (605) to perform envelope adjustment on the operating spectrum portion.

4. The device according to claim 1, in, The analyzer is configured to detect the artifact generating signal portion at a specific frequency, and wherein the operator is configured to control the frequency tiling generator (820) so that the frequency tiling generator (820) is configured to change the frequency boundary of the spectrum portion of the decoded core signal or the frequency boundary of the regenerated spectrum portion, thereby causing the artifact generating signal portion to generate less artifact or no artifact.

5. A device for decoding an encoded audio signal comprising an encoded core signal and parametric data (605), comprising: A core decoder (600) for decoding the encoded core signal to obtain a decoded core signal; An analyzer, configured to analyze the decoded core signal or the preliminary regenerated signal (703) to provide an analysis result (603); as well as a frequency regenerator (604) for regenerating a portion of the spectrum not included in the decoded core signal using the portion of the spectrum of the decoded core signal, the parameterized data (605) and the analysis result (603), Wherein, the analyzer is configured to detect a portion of the tone signal (802) located in a frequency detection range, wherein the frequency detection range extends a predetermined detection bandwidth from a frequency boundary of a reconstruction range or between adjacent frequency tiles within the reconstruction range, and the predetermined detection bandwidth is less than 20% of the bandwidth of the source frequency range or the reconstruction range, or the predetermined detection bandwidth is 1 bark.

6. The device according to claim 5, comprising an operator for operating the preliminary regeneration signal (703), in, The operator is configured to attenuate or remove (708) a spectral portion of the predetermined detection bandwidth including the tone signal portion (802) of the preliminary regenerated signal (703).

7. The device according to claim 6, in, The operator is configured to: determine a starting spectral portion located in frequency at a starting frequency of the tone signal portion (802) and determine an ending spectral portion located in frequency at an ending frequency of the tone signal portion (802); interpolate (804) between the starting frequency and the ending frequency to obtain an interpolated signal portion; and replace the tone signal portion (802) between the starting frequency and the ending frequency with the interpolated signal portion (806).

8. The device according to claim 6, in, The operator is configured to randomly or non-randomly generate spectral lines (808), the energy of which is determined by a non-tonal signal portion of the decoded core signal or a non-tonal signal portion of the regenerated spectral portion (810).

9. A device for decoding an encoded audio signal comprising an encoded core signal and parametric data (605), comprising: A core decoder (600) for decoding the encoded core signal to obtain a decoded core signal; An analyzer, configured to analyze the decoded core signal or the preliminary regenerated signal (703) to provide an analysis result (603); as well as a frequency regenerator (604) for regenerating a portion of the spectrum not included in the decoded core signal using the portion of the spectrum of the decoded core signal, the parameterized data (605) and the analysis result (603), wherein the frequency regenerator (604) comprises a frequency tile generator (820), wherein the frequency tile generator (820) is configured to generate a first frequency tile for a first frequency spectrum portion and a second frequency tile for a second frequency spectrum portion using the same or different frequency spectrum portions of the decoded core signal; Wherein, the lower frequency boundary of the second frequency tiling is consistent with the upper frequency boundary of the first frequency tiling; wherein the analyzer is configured to detect whether a peak frequency spectrum portion is clipped by a lower frequency boundary of the second frequency tile or an upper frequency boundary of the first frequency tile or a lower frequency boundary of the first frequency tile and a predetermined gap filling start frequency (309) of the decoding core signal; and The apparatus further comprises an operator configured to control the frequency tile generator (820) so that the frequency tile generator (820) generates a modified frequency tile in which a start frequency boundary or an end frequency boundary is modified, so that the clipping is reduced or eliminated.

10. A device for decoding an encoded audio signal comprising an encoded core signal and parametric data (605), comprising: A core decoder (600) for decoding the encoded core signal to obtain a decoded core signal; An analyzer, configured to analyze the decoded core signal or the preliminary regenerated signal (703) to provide an analysis result (603); as well as a frequency regenerator (604) for regenerating a portion of the spectrum not included in the decoded core signal using the portion of the spectrum of the decoded core signal, the parameterized data (605) and the analysis result (603), wherein the core decoder (600) is configured to obtain frequency domain decoded spectral portions, the frequency domain decoded spectral portions comprising a first group of first spectral portions represented by spectral values ​​different from a zero representation of spectral values, and wherein a second group of second spectral portions are represented by the zero representation of the spectral values, the first group of first spectral portions representing the decoded core signal, wherein said parameterized data (605) is provided for said second set of second spectral portions, wherein the frequency regenerator (604) is configured to use decoded spectrum portions from the first set of first spectrum portions to regenerate spectrum portions within the reconstruction band that are not included in the first set of first spectrum portions to obtain regenerated spectrum portions, and Therein, the device further comprises a frequency-to-time converter (828) for converting the regenerated spectrum portion and the decoded core signal into a time representation.

11. The device according to claim 10, in, The core decoder (600) is configured to output a modified discrete cosine transform (MDCT) spectrum value; and The frequency-to-time converter (828) includes a processor configured to perform an inverse MDCT transform (512, 514, 516) applying an overlap-add process to subsequently obtained MDCT frames.

12. A device for decoding an encoded audio signal comprising an encoded core signal and parametric data (605), comprising: A core decoder (600) for decoding the encoded core signal to obtain a decoded core signal; An analyzer, configured to analyze the decoded core signal or the preliminary regenerated signal (703) to provide an analysis result (603); as well as a frequency regenerator (604) for regenerating a portion of the spectrum not included in the decoded core signal using the portion of the spectrum of the decoded core signal, the parameterized data (605) and the analysis result (603), Wherein, the frequency regenerator (604) is configured to: generating (702) the preliminary regeneration signal (703); detecting (704) a tonal component (708) in the preliminary regenerated signal (703); adjusting a transition frequency between a source range and a reconstruction range or between adjacent frequency tiles in the reconstruction range based on a result of the detection (704) to generate a regenerated signal; and removing the tonal component in a detection range around the transition frequency (708); Wherein, the frequency regenerator (604) further comprises: a crossover filter (710) for crossover filtering the signal from which tonal components in a crossover range around the transition frequency are removed; and A spectral envelope shaper (712) is used to perform spectral envelope shaping on a result of the cross filtering using the parameterized data (605).

13. A method for decoding an encoded audio signal comprising an encoded core signal and parametric data (605), comprising: Decoding (600) the encoded core signal to obtain a decoded core signal; Analyzing the decoded core signal or the preliminary regenerated signal (703) to provide an analysis result (603); and regenerating (604) a portion of the spectrum not included in the decoded core signal using the spectral portion of the decoded core signal, the parameterized data (605) and the analysis result (603), wherein the analyzing (704) comprises detecting a portion of the tone signal (802) located in a frequency detection range, wherein the frequency detection range extends from a frequency boundary of a reconstruction range or between adjacent frequency tiles within the reconstruction range by a predetermined detection bandwidth, wherein the predetermined detection bandwidth is less than 20% of a bandwidth of the source frequency range or of the reconstruction range, or the predetermined detection bandwidth is 1 bark, or wherein the regeneration (604) comprises generating a first frequency tile for a first frequency tile and a second frequency tile for a second frequency tile using the same or different frequency spectral portions of the decoding core signal, wherein the lower frequency boundary of the second frequency tile coincides with the upper frequency boundary of the first frequency tile, wherein the analysis (704) comprises detecting whether a peak frequency spectral portion is clipped by the lower frequency boundary of the second frequency tile or the upper frequency boundary of the first frequency tile or the lower frequency boundary of the first frequency tile and a predetermined gap filling start frequency (309) of the decoding core signal; and further comprising controlling the generation of the first frequency tile and the second frequency tile so that a modified frequency tile in which the start frequency boundary or the end frequency boundary is modified is generated, thereby reducing or eliminating the clipping, or wherein the decoding (600) comprises obtaining frequency domain decoded spectral portions, the frequency domain decoded spectral portions comprising a first group of first spectral portions represented by spectral values ​​different from a zero representation of the spectral values, and wherein a second group of second spectral portions are represented by the zero representation of the spectral values, the first group of first spectral portions representing the decoded core signal, wherein the parameterized data (605) is provided for the second group of second spectral portions, wherein the regeneration (604) comprises using decoded spectral portions from the first group of first spectral portions to regenerate spectral portions within a reconstructed band that are not included in the first group of first spectral portions to obtain regenerated spectral portions, and wherein the method further comprises: converting the regenerated spectral portions and the decoded core signal into a time representation, or Wherein, the regeneration (604) includes generating (702) the preliminary regeneration signal (703), detecting (704) the tonal component (708) in the preliminary regeneration signal (703); adjusting the transition frequency between the source range and the reconstruction range or between adjacent frequency tiles in the reconstruction range based on the result of the detection (704) to generate a regeneration signal; and removing the tonal component (708) in the detection range around the transition frequency, and wherein, the regeneration (604) further includes: cross-filtering the signal from which the tonal component in the cross-range around the transition frequency has been removed; and using the parameterized data (605) to perform spectral envelope shaping on the result of the cross-filtering.

14. A method for decoding an encoded audio signal comprising an encoded core signal and parametric data (605), comprising: Decoding (600) the encoded core signal to obtain a decoded core signal; analyzing (704) the preliminary reproduced signal (703) to detect an artifact generating signal portion as an analysis result (603); and regenerating (604) a portion of the spectrum not included in the decoded core signal using the spectral portion of the decoded core signal, the parameterized data (605) and the analysis result (603), Wherein, the regeneration (604) includes operating the preliminary regeneration signal (703) or performing additional regeneration using parameters different from the parameters used to generate the preliminary regeneration signal (703) to reduce or eliminate the artifact generating signal portion in the preliminary regeneration signal (703), wherein the operation is controlled by the analysis (704).

15. A computer readable medium having a computer program stored thereon, the computer program executing the method according to claim 13 or the method according to claim 14 when the computer program is run on a computer or a processor.

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