Noise Update Circuit

Abstract

To provide a noise update circuit that estimates noise components accurately, and is used in a noise reduction circuit.SOLUTION: A noise update circuit has: a first update unit 111 that calculates a post-update noise spectrum when a frame to be processed is a frame including only noise components; and a second update unit 112 that calculates a post-update noise spectrum when the frame to be processed is a frame including voice components.EFFECT: Even when the frames including voice components are continued one after another as the frames to be processed, fluctuation of noise can be followed, and noise components can be accurately estimated.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to a noise updating circuit, and more particularly to a noise updating circuit that can be used in a noise reduction circuit incorporated in, for example, a wireless device that transmits and receives high-frequency signals. [Background technology]

[0002] Spectral subtraction is known as a method for suppressing noise components contained in an audio signal (see, for example, Patent Document 1 and Non-Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 4-238399 [Non-patent literature]

[0004] [Non-Patent Document 1] P. Scalart and J. Vieira Filho, "Speech Enhancement Based on a Priori Signal to Noise Estimation", IEEE International Conference on. Acoustics, Speech, Signal Processing, Atlanta, GA, USA, vol. 2, pp. 629-632, 1996. Summary of the Invention [Problem to be solved by the invention]

[0005] In order to properly apply the spectral subtraction method, it is important to accurately estimate the noise components and subtract them from the input speech signal.

[0006] SUMMARY OF THE PRESENT EMBODIMENT An object of the present invention is to provide a noise updating circuit capable of accurately estimating a noise component. [Means for solving the problem]

[0007] In order to solve the above problem, the present invention provides a first updating unit that, when a frame to be processed is a frame containing only noise components, calculates an updated noise spectrum Ni(f) for each frequency f in accordance with the following formula 1 which is an IIR filter or the following formula 2 which is an FIR filter, using a signal corresponding to an amplitude spectrum of the frame to be processed as an input signal spectrum Yi(f) (where Ni-1(f): noise spectrum one frame before the update, Yi-j(f): input signal spectrum j frames before the update, Kn: constant that determines weighting of Ni-1(f) with respect to Yi(f) in the case where the frame to be processed is a frame containing only noise components, i: ordinal number that represents the order in the time series, j: integer of 0 or more that represents the degree of distance from ordinal number i in the time series);

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[0013] Claim 2 The invention described in claim 1 In the noise updating circuit described in , the constant Ks is set to any value within a range corresponding to 1 to 10 seconds, which is the time constant of an IIR filter or the averaging interval of an FIR filter.

[0015] Claim 3 The invention described in claim 1 The noise updating circuit according to claim 1, wherein the coefficient Te is set to any value within a range of 1 to 100. Effect of the Invention

[0018] According to the invention as recited in claim 1, even if a series of frames containing voice components are processed, it is possible to track noise fluctuations and accurately estimate the noise components. Specifically, in a conventional circuit that realizes the spectral subtraction method, the noise spectrum is updated when a series of frames containing only noise components are processed, but the noise spectrum is not updated when a series of frames containing voice components are processed. This causes a problem that if a series of frames containing voice components are processed, the noise spectrum is not updated and it is not possible to accurately track noise fluctuations, and as a result, it is not possible to accurately estimate the noise components. In response to this, the invention as recited in claim 1 In the invention described in the above, the noise spectrum is updated even when the frame to be processed is a frame containing a voice component. Therefore, even if a series of frames containing voice components are being processed, it is possible to track noise fluctuations and accurately estimate the noise components. Furthermore, according to the invention as recited in claim 1, it is possible to avoid suppressing tone signals. Specifically, in conventional circuits that realize the spectral subtraction method, components that are constantly present in the frequency spectrum are judged as noise and suppressed, so tone signals are also judged as noise due to their stationary nature and are subject to suppression, resulting in the problem that tone signals necessary for the user (for example, Morse code) are also suppressed. In contrast, according to the invention as recited in claim 1, frequency components whose amplitude spectrum is significantly larger than the average spectrum level are excluded from updating of the noise spectrum, making it possible to avoid suppressing tone signals.

[0019] Claim 2According to the invention described in the above, when the frame to be processed is a frame containing a voice component, the constant Ks that determines the weighting of the noise spectrum Ni-1(f) of the previous frame to be updated for the input signal spectrum Yi(f) is set to an appropriate value. Therefore, it is possible to more reliably follow noise fluctuations when frames containing voice components are successively processed as frames to be processed, and it is possible to more reliably and accurately estimate the noise components.

[0021] Claim 3 According to the invention described in the above, the coefficient Te is set to an appropriate value, so that it is possible to more reliably exclude frequency components whose amplitude spectrum is significantly larger than the average spectrum level from updating of the noise spectrum, and it is possible to more reliably prevent tone signals from being suppressed. [Brief description of the drawings]

[0022] [Figure 1] 1 is a functional block diagram showing a schematic configuration of a noise reduction circuit including a noise updating circuit according to an embodiment of the present invention; [Diagram 2] 1 is a functional block diagram showing a schematic configuration of a noise updating circuit according to a first embodiment. [Diagram 3] FIG. 11 is a functional block diagram showing a schematic configuration of a noise updating circuit according to a second embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0023] Hereinafter, the present invention will be described based on the illustrated embodiment.

[0024] (Embodiment 1) Fig. 1 is a functional block diagram showing a schematic configuration of a noise reduction circuit 1 including a noise updating circuit 11 according to an embodiment of the present invention. Fig. 2 is a functional block diagram showing a schematic configuration of the noise updating circuit 11 according to the first embodiment.

[0025] The noise reduction circuit 1 is a circuit that is incorporated, for example, in a radio device that transmits and receives high-frequency signals, and realizes Spectral Subtraction, which is a method for suppressing noise components contained in an audio signal. The noise reduction circuit 1 mainly includes a pre-emphasis circuit 2, a window processing unit 3, a time-frequency conversion unit 4, a conversion result output unit 5, a subtraction unit 6, a synthesis unit 7, a frequency-time conversion unit 8, a de-emphasis circuit 9, a voice activity detection unit 10, and a noise updating circuit 11.

[0026] A pre-emphasis (PE) circuit 2 performs high-frequency emphasis processing for amplifying the relative intensity of high-frequency components in advance on an audio signal obtained by demodulating a high-frequency signal received from an antenna, and outputs the signal after high-frequency emphasis processing.

[0027] The window processing unit 3 receives the high-frequency emphasis processed signal output from the pre-emphasis circuit 2, extracts frames of a predetermined length from the input signal (e.g., extracts a time waveform of 25 ms every 12.5 ms), and performs window processing on each frame by multiplying it by a window function such as a Hanning window. The window processing unit 3 outputs the windowed frame each time it performs window processing on each frame.

[0028] The time-frequency conversion unit 4 receives a windowed frame output from the window processing unit 3, and each time the time-frequency conversion unit 4 receives a frame, it performs a conversion process from a time domain signal to a frequency domain signal, calculates a frequency spectrum including amplitude components and phase components for each of a plurality of frequencies, and outputs a signal of a frequency spectrum of real and imaginary numbers. The time-frequency conversion unit 4 performs a time-frequency conversion by, for example, a Discrete Fourier Transform or a Fast Fourier Transform to calculate the frequency spectrum.

[0029] The conversion result output unit 5 receives an input of a frequency spectrum signal for each frame (for example, at intervals of about 12.5 ms) output from the time-frequency conversion unit 4, and outputs, for each frame, a signal corresponding to an amplitude spectrum including amplitude components of each frequency in the input frequency spectrum to a subtraction unit 6, and outputs a signal corresponding to a phase spectrum including phase components of each frequency in the input frequency spectrum to a synthesis unit 7.

[0030] The subtraction unit 6 receives an input of a signal corresponding to the amplitude spectrum for each frame output from the conversion result output unit 5, and also receives an input of a signal corresponding to the updated noise spectrum for each frame output from the noise update circuit 11, and subtracts the signal corresponding to the input updated noise spectrum for each frequency (in other words, for each spectrum) from the signal corresponding to the input amplitude spectrum for each frame. This suppresses the noise components contained in the audio signal. The subtraction unit 6 outputs a signal corresponding to the amplitude spectrum after subtraction for each frame output from the conversion result output unit 5.

[0031] The synthesis unit 7 receives an input of a signal corresponding to the phase spectrum for each frame output from the conversion result output unit 5, and also receives an input of a signal corresponding to the amplitude spectrum after the subtraction process for each frame output from the subtraction unit 6, synthesizes the input signal corresponding to the phase spectrum and the signal corresponding to the amplitude spectrum for each frame to generate a frequency spectrum, and outputs a signal with a frequency spectrum of real and imaginary numbers.

[0032] The frequency-time transform unit 8 receives the frequency spectrum signal for each frame output from the synthesis unit 7, and performs a transform process from a frequency domain signal to a time domain signal for each frame on the input frequency spectrum signal, i.e., an inverse transform process of the transform process in the time-frequency transform unit 4, to output an audio signal. The frequency-time transform unit 8 performs frequency-time transform, for example, by inverse discrete Fourier transform or inverse fast Fourier transform, to generate an audio signal.

[0033] The de-emphasis (DE) circuit 9 receives the audio signal output from the frequency-time conversion unit 8, performs high-frequency attenuation processing on the input audio signal to attenuate the relative intensity of high-frequency components, i.e., attenuation processing using the inverse filter of the pre-emphasis circuit 2, and outputs the audio signal after high-frequency attenuation processing.

[0034] The voice activity detection unit 10 receives an input of a signal corresponding to the amplitude spectrum for each frame output and branched from the conversion result output unit 5, and judges for each frame, with respect to the input signal corresponding to the amplitude spectrum, whether it is a frame containing only noise components or a frame including voice components.

[0035] The method used by the voice activity detection unit 10 to determine whether a frame to be processed contains only noise components or also contains voice components is not limited to a specific procedure or technique, but may be appropriately selected from conventional or new procedures or techniques.

[0036] As a method for determining whether a frame to be processed contains only noise components or also contains voice components in the voice section detection unit 10, for example, a method that focuses on the non-constancy of voice and determines that the frame to be processed contains only noise components if the average or variance value of the amplitude magnitude for each frequency of the amplitude spectrum is less than a predetermined threshold value multiple times (e.g., about 3 to 5 times) consecutively in the most recent frame, and determines that the frame to be processed contains voice components in other cases; or a method that determines that the frame to be processed contains only noise components if the average or variance value of the amplitude magnitude for each frequency of the amplitude spectrum is less than a predetermined threshold value, and determines that the frame to be processed contains voice components if the average or variance value is equal to or greater than the threshold value.

[0037] The voice activity detection unit 10 outputs a noise frame signal when it determines that the frame to be processed contains only noise components, and outputs a voice frame signal when it determines that the frame to be processed contains voice components. The voice activity detection unit 10 outputs a noise frame signal or a voice frame signal as the voice activity detection result for each frame.

[0038] The noise updating circuit 11 according to the embodiment has a first updating unit that, when the frame to be processed is a frame containing only noise components, uses a signal corresponding to the amplitude spectrum of the frame to be processed as an input signal spectrum Yi(f) and calculates an updated noise spectrum Ni(f) for each frequency f by processing including averaging (where i is an ordinal number indicating the order in time series), and a second updating unit that, when the frame to be processed is a frame containing a voice component, calculates an updated noise spectrum Ni(f) for each frequency f by processing including averaging, such that the averaging time of the input signal spectrum Yi(f) when calculating the updated noise spectrum Ni(f) when the frame contains a voice component is longer than the averaging time of the input signal spectrum Yi(f) when calculating the updated noise spectrum Ni(f) when the frame contains only noise components.

[0039] The noise update circuit 11 updates a noise spectrum representing noise components for each frequency previously calculated to the latest noise spectrum by adding the amplitude spectrum of the current frame (in other words, the frame to be processed, the latest frame), and has a first update unit 111 and a second update unit 112.

[0040] The noise update circuit 11 receives an input of a signal corresponding to the amplitude spectrum for each frame output from the conversion result output unit 5 and branched, and also receives an input of the voice activity detection result for each frame output from the voice activity detection unit 10, and updates the noise spectrum Ni-1(f) of the previous frame for each frequency f using the input signal corresponding to the amplitude spectrum, and calculates the updated noise spectrum Ni(f) according to the content of the input voice activity detection result according to the following formula 7 or 8, or 9 or 10. Note that the subscript i in the following formulas is an ordinal number representing the order in time series, and represents an order commonly applied to all formulas. Also, the subscript j in the following formulas is a variable representing the degree of distance from the ordinal number i in the time series, and is an integer equal to or greater than 0.

[0041] When the voice activity detection result input to the noise updating circuit 11 is a noise frame signal, a first updating unit 111 calculates an updated noise spectrum Ni(f) for each frequency f using the signal corresponding to the input amplitude spectrum as an input signal spectrum Yi(f) according to the following formula 7 which is an IIR (abbreviation of infinite impulse response) filter or the following formula 8 which is an FIR (abbreviation of finite impulse response) filter. Note that in the following formulas, Ni-1(f) represents the noise spectrum one frame before the update, and Yi-j(f) represents the input signal spectrum j frames before the update.

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[0042] Kn in Equation 7 and Equation 8 is a constant that determines the weighting of the noise spectrum Ni-1(f) of the previous frame to the input signal spectrum Yi(f), which is the amplitude spectrum of the frame to be processed (in other words, the current frame or the latest frame) when the frame contains only noise components, and is referred to as the "noise pre-update weighting constant Kn."

[0043] The noise pre-update weighting constant Kn is not limited to a specific value as long as it is an integer equal to or greater than 0. Specifically, the noise pre-update weighting constant Kn may be set to any value within a range equivalent to the time constant of an IIR filter or the average interval of an FIR filter of about 0.06 to 0.20 seconds (for example, a range of about Kn=5 to 16 at a frame interval of 12.5 ms), and may be set to a value equivalent to the time constant of an IIR filter or the average interval of an FIR filter of about 0.1 seconds (for example, about Kn=8 at a frame interval of 12.5 ms). Note that when the time constant of an IIR filter or the average interval of an FIR filter is set to, for example, 0.1 seconds, the specific value of the constant Kn in Equation 7 is different from the specific value of the constant Kn in Equation 8.

[0044] When the voice activity detection result input to the noise updating circuit 11 is a voice frame signal, a second updating unit 112 calculates an updated noise spectrum Ni(f) for each frequency f, using the signal corresponding to the input amplitude spectrum as an input signal spectrum Yi(f) in accordance with the following Equation 9 which is an IIR filter or the following Equation 10 which is an FIR filter.

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[0045] Ks in Equation 9 and Equation 10 is a constant that determines the weighting of the noise spectrum Ni-1(f) of the previous frame to be updated to the input signal spectrum Yi(f), which is the amplitude spectrum of the frame to be processed (in other words, the current frame or the latest frame), when the frame contains a voice component, and is referred to as the "weighting constant Ks before voice update."

[0046] The pre-update weight constant Ks during voice is not limited to a specific value, as long as it is a larger integer than the pre-update weight constant Kn during noise, and preferably a sufficiently large integer. Specifically, the pre-update weight constant Ks during voice may be set to any value within a range equivalent to about 1 to 10 seconds of the time constant of the IIR filter or the average interval of the FIR filter (for example, a range of about Ks=80 to 800 at a frame interval of 12.5 ms), more specifically, to any value within a range equivalent to about 1 to 6 seconds of the time constant of the IIR filter or the average interval of the FIR filter (for example, a range of about Ks=80 to 500 at a frame interval of 12.5 ms), and particularly to a value equivalent to about 3.7 seconds of the time constant of the IIR filter or the average interval of the FIR filter (for example, about Ks=295 at a frame interval of 12.5 ms). Note that when the time constant of the IIR filter or the average interval of the FIR filter is set to, for example, 3.7 seconds, the specific value of the constant Ks in Equation 9 is different from the specific value of the constant Ks in Equation 10.

[0047] By setting the pre-update weighting constant Ks for speech to a sufficiently large value, speech components are prevented from being significantly reflected in the update of the noise spectrum due to the non-constant nature of speech, and therefore the speech components are not suppressed as noise components.

[0048] In addition, when an IIR filter (general form is Ni(f)=ΣAjYi-j(f)+ΣBkNi-k(f); where A and B are coefficients, i is an ordinal number representing the order of the time series, j is an integer of 0 or more representing the degree of separation from the ordinal number i in the time series, and k is an integer of 1 or more representing the degree of separation from the ordinal number i in the time series) is used as the averaging process for calculating the updated noise spectrum Ni(f), the first updating unit 111 calculates the updated noise spectrum Ni(f) for each frequency f by processing including averaging when the frame to be processed is a frame containing only noise components, using a signal corresponding to the amplitude spectrum of the frame to be processed as the input signal spectrum Yi(f), and calculates the updated noise spectrum Ni(f) for each frequency f by processing including averaging when the frame to be processed is a frame containing speech components. and a second updating unit 112 that calculates the updated noise spectrum Ni(f) by processing including averaging, and this corresponds to the case where the averaging time for averaging the input signal spectrum Yi(f), the past input signal spectrum Yi-j(f), and the past noise spectrum Ni-k(f) when calculating the updated noise spectrum Ni(f) for a frame including a voice component is longer than the averaging time for averaging the input signal spectrum Yi(f), the past input signal spectrum Yi-j(f), and the past noise spectrum Ni-k(f) when calculating the updated noise spectrum Ni(f) for a frame containing only a noise component.

[0049] Furthermore, in the case of using an IIR filter in which Aj=0 for j≧1 for the general form of the above IIR filter, a first updating unit 111 is provided for calculating an updated noise spectrum Ni(f) for each frequency f by processing including averaging, using a signal corresponding to the amplitude spectrum of the frame to be processed as an input signal spectrum Yi(f) when the frame to be processed is a frame containing only noise components, and a second updating unit 112 is provided for calculating an updated noise spectrum Ni(f) for each frequency f by processing including averaging when the frame to be processed is a frame containing a voice component, and this corresponds to the case where the averaging time for averaging the input signal spectrum Yi(f) and past noise spectrum Ni-k(f) when calculating the updated noise spectrum Ni(f) when the frame contains a voice component is longer than the averaging time for averaging the input signal spectrum Yi(f) and past noise spectrum Ni-k(f) when calculating the updated noise spectrum Ni(f) when the frame contains only noise components.

[0050] For the general form of the IIR filter above, assuming Aj=0 for j≧1, the case where A0=1 / (1+Kn), B1=Kn / (1+Kn), and Bk=0 (k≧2) corresponds to the above formula 7, and the case where A0=1 / (1+Ks), B1=Ks / (1+Ks), and Bk=0 (k≧2) corresponds to the above formula 9.

[0051] Furthermore, when an FIR filter (general form is Ni(f)=ΣAjYi-j(f); where A is a coefficient, i is an ordinal number representing the order of the time series, and j is an integer equal to or greater than 0 representing the degree of separation from the ordinal number i in the time series; that is, the general form of the IIR filter described above with Bk=0) is used as the averaging process for calculating the updated noise spectrum Ni(f), a first updating unit 111 is provided which, when the frame to be processed is a frame containing only noise components, calculates the updated noise spectrum Ni(f) for each frequency f by processing including averaging using a signal corresponding to the amplitude spectrum of the frame to be processed as the input signal spectrum Yi(f); and In some cases, the system includes a second updating unit 112 that calculates an updated noise spectrum Ni(f) for each frequency f by processing including averaging, and the averaging time for averaging the input signal spectrum Yi(f) and past input signal spectra Yi-j(f) when calculating the updated noise spectrum Ni(f) for a frame including a voice component is longer than the averaging time for averaging the input signal spectrum Yi(f) and past input signal spectra Yi-j(f) when calculating the updated noise spectrum Ni(f) for a frame including only a noise component.

[0052] Regarding the general form of the above FIR filter, when Aj=1 / Kn it corresponds to the above formula 8, and when Aj=1 / Ks it corresponds to the above formula 10.

[0053] Every time the noise updating circuit 11 receives the signal corresponding to the amplitude spectrum for each frame and the voice activity detection result, it outputs a signal corresponding to the updated noise spectrum Ni(f) for each frequency f to the subtraction unit 6. The subtraction unit 6 performs a process of subtracting the signal corresponding to the updated noise spectrum Ni(f) from the signal corresponding to the amplitude spectrum output from the conversion result output unit 5, using the signal corresponding to the updated noise spectrum Ni(f) output from the noise updating circuit 11 for each frame.

[0054] According to the above-mentioned noise updating circuit 11, even if the frames to be processed are successive frames containing voice components, it is possible to follow the noise fluctuations and accurately estimate the noise components. Specifically, in a conventional circuit that realizes the spectrum subtraction method, the noise spectrum is updated when the frames to be processed are frames containing only noise components, but the noise spectrum is not updated when the frames to be processed are frames containing voice components. Therefore, if the frames to be processed are successive frames containing voice components, the noise spectrum is not updated, so it is not possible to follow the noise fluctuations accurately, and as a result, it is not possible to accurately estimate the noise components. In contrast, according to the above-mentioned noise updating circuit 11, the noise spectrum is updated even when the frames to be processed are frames containing voice components, so it is possible to follow the noise fluctuations and accurately estimate the noise components even if the frames to be processed are successive frames containing voice components.

[0055] (Embodiment 2) FIG. 3 is a functional block diagram showing a schematic configuration of the noise updating circuit 11 according to the second embodiment of the present invention.

[0056] This embodiment differs from embodiment 1 in that the noise updating circuit 11 has an additional configuration compared to the configuration of embodiment 1 described above. However, there are also common configurations and processing contents, and the same configurations and processing contents as embodiment 1 will be denoted by the same reference numerals and their description will be omitted.

[0057] The noise updating circuit 11 according to this embodiment further includes an average calculation unit 113 that calculates an average spectrum level M for the input signal spectrum Yi(f), and a third updating unit 114 that determines an updated noise spectrum Ni(f) for a frequency f where Yi(f)≧Te×M with respect to the input signal spectrum Yi(f) and the average spectrum level M.

[0058] The noise updating circuit 11 receives an input of a signal corresponding to the amplitude spectrum for each frame output from the conversion result output unit 5 and branched, and also receives an input of the voice activity detection result for each frame output from the voice activity detection unit 10. Using the input signal corresponding to the amplitude spectrum, the noise updating circuit 11 updates the noise spectrum Ni-1(f) of the frame before the update for each frequency f, and calculates the updated noise spectrum Ni(f) according to any one of the above-mentioned Formula 7 or 8, Formula 9 or 10, and Formula 12 depending on the content of the input voice activity detection result, etc.

[0059] The average value calculation unit 113 calculates an average spectrum level M according to the following formula 11, using the signal corresponding to the amplitude spectrum for each frame output and branched from the conversion result output unit 5 as the input signal spectrum Yi(f). The average spectrum level M is the average value in the frequency axis direction of the amplitude spectrum.

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[0060] In Equation 11, f represents a frequency in the amplitude spectrum, f1 is the minimum frequency in the amplitude spectrum, f2 is the maximum frequency in the amplitude spectrum, and Fn represents the number of frequencies in the range from the minimum frequency f1 to the maximum frequency f2. In other words, the number of frequencies Fn is n / 2+1, where n is the number of sample points included in one frame in the time-frequency conversion by the time-frequency conversion unit 4.

[0061] The average value calculation section 113 calculates an average spectrum level M every time a signal corresponding to the amplitude spectrum of each frame is input.

[0062] Furthermore, when the voice section detection result input to the noise update circuit 11 is a noise frame signal, for each frequency f, the signal corresponding to the input amplitude spectrum is used as the input signal spectrum Yi(f), and the following process or is performed according to the relationship between the input signal spectrum Yi(f) and the average spectrum level M.

[0063] For a frequency f where Yi(f) < Te × M The first update unit 111 calculates the updated noise spectrum Ni(f) according to the above formula 7 or formula 8.

[0064] Te in the relationship between the input signal spectrum Yi(f) and the average spectrum level M is a coefficient for excluding frequency components whose amplitude spectrum is significantly larger than the average spectrum level M from the update of the noise spectrum. The coefficient Te is not limited to a specific value. For example, considering that frequency components corresponding to tone signals are excluded from the update of the noise spectrum so that the tone signals are not subtracted by the subtraction unit 6 and are not suppressed as noise components, it is appropriately set to an appropriate value. Specifically, the coefficient Te is considered to be set to any value in the range of about 1 to 100, and particularly considered to be set to about 10.

[0065] For a frequency f where Yi(f) ≥ Te × M The third update unit 114 determines the updated noise spectrum Ni(f) according to the following formula 12.

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[0066] Ni-1(f) in formula 12 represents the noise spectrum one frame before the update.

[0067] Also, when the voice section detection result input to the noise update circuit 11 is a voice frame signal, for each frequency f, using the signal corresponding to the input amplitude spectrum as the input signal spectrum Yi(f), the following processing or <E> is performed according to the relationship between the input signal spectrum Yi(f) and the average spectrum level M.

[0068] For the frequency f where Yi(f) < Te × M The second update unit 112 calculates the updated noise spectrum Ni(f) according to the above formula 9 or formula 10.

[0069] <E> For the frequency f where Yi(f) ≥ Te × M The third update unit 114 determines the updated noise spectrum Ni(f) according to the above formula 12.

[0070] In the above processing, that is, for the frequency component where Yi(f) ≥ Te × M and the amplitude spectrum is significantly larger than the average spectrum level M, the noise spectrum Ni(f) after the update is excluded from the update and remains the noise spectrum Ni−1(f) one frame before the update.

[0071] Each time the noise update circuit 11 receives an input of a signal corresponding to the amplitude spectrum for each frame and a voice section detection result, it outputs a signal corresponding to the updated noise spectrum Ni(f) for each frequency f to the subtraction unit 6. The subtraction unit 6 performs a process of subtracting the signal corresponding to the updated noise spectrum Ni(f) from the signal corresponding to the amplitude spectrum output from the conversion result output unit 5 using the signal corresponding to the updated noise spectrum Ni(f) output from the noise update circuit 11 for each frame.

[0072] The above-described noise updating circuit 11 makes it possible not to suppress tone signals. Specifically, in conventional circuits that realize the spectral subtraction method, components that are constantly present in the frequency spectrum are judged to be noise and suppressed, so tone signals are also judged to be noise due to their stationary nature and are subject to suppression, resulting in the problem that tone signals necessary for users (e.g., Morse code) are also suppressed. In contrast, the above-described noise updating circuit 11 excludes frequency components whose amplitude spectrum is significantly larger than the average spectrum level from the noise spectrum update, making it possible not to suppress tone signals.

[0073] In addition, with respect to the noise updating circuit 11 according to the second embodiment, the manner in which the noise spectrum is updated may be adjusted to adjust the manner in which the noise components are suppressed, in accordance with the mode selection in which the user selects whether or not to activate the average value calculation unit 113 and the third update unit 114 depending on the operation at the time. For example, when the user mainly transmits and receives voice signals while suppressing noise components, the user may select a mode in which the average value calculation unit 113 and the third update unit 114 are not activated to suppress tone signals, whereas when transmitting and receiving Morse codes, the user may select a mode in which the average value calculation unit 113 and the third update unit 114 are activated to not suppress tone signals.

[0074] Although the embodiment of the present invention has been described above, the specific configuration is not limited to the above embodiment, and even if there are design changes within the scope of the present invention, they are included in the present invention. For example, the above embodiment is described by taking as an example a case in which the noise updating circuit 11 according to the present invention is applied to the noise reduction circuit 1 whose schematic configuration is shown in FIG. 1, but the configuration of the noise reduction circuit to which the present invention can be applied is not limited to the example shown in FIG. 1. Furthermore, the circuits to which the present invention can be applied are not limited to noise reduction circuits. In other words, the present invention can be applied to various circuits in which it is necessary to update the noise spectrum in a time series.

[0075] Furthermore, the process including averaging for calculating the updated noise spectrum Ni(f) may be any method that uses coefficients equivalent to the noise pre-update weighting constant Kn and the voice pre-update weighting constant Ks in the above embodiment. That is, the calculation formula for the updated noise spectrum Ni(f) is not limited to the formulas 7 to 10 in the above embodiment. [Explanation of symbols]

[0076] 1 Noise reduction circuit 2 Pre-emphasis circuit 3 Window processing section 4 Time-frequency transform section 5. Conversion result output section 6 Subtraction section 7. Synthesis section 8 Frequency-time conversion section 9 De-emphasis circuit 10 Voice Activity Detector 11 Noise Update Circuit 111 First Update 112 Second Update 113 Average value calculation unit (second embodiment) 114 Third update unit (second embodiment)

Claims

1. a first updating unit that, when a frame to be processed is a frame containing only noise components, calculates an updated noise spectrum Ni(f) for each frequency f according to the following Equation 1 which is an IIR filter or the following Equation 2 which is an FIR filter, using a signal corresponding to an amplitude spectrum of the frame to be processed as an input signal spectrum Yi(f) (where Ni-1(f): noise spectrum one frame before the update, Yi-j(f): input signal spectrum j frames before the update, Kn: constant determining weighting of Ni-1(f) with respect to Yi(f) when the frame to be processed is a frame containing only noise components, i: ordinal number representing the order in the time series, j: integer equal to or greater than 0 representing the degree of distance from ordinal number i in the time series); [0010] [0025] a second update unit that calculates an updated noise spectrum N(f) for each frequency f according to the following Equation 3 which is an IIR filter or the following Equation 4 which is an FIR filter when the frame to be processed is a frame including a voice component (where Ks is a constant that determines the weighting of N(f) with respect to Y(f) when the frame to be processed is a frame including a voice component, Kn<Ks); [0030] [0045] having an average calculation unit that calculates an average spectrum level M for the input signal spectrum Y(f) according to the following formula 5 (where f1 is the minimum frequency in the amplitude spectrum, f2 is the maximum frequency in the amplitude spectrum, and Fn is the number of frequencies in the range from the minimum frequency f1 to the maximum frequency f2); [0050] a third update unit that determines an updated noise spectrum Ni(f) according to the following Equation 6 for a frequency f where Yi(f)≧Te×M with respect to the input signal spectrum Yi(f) and the average spectrum level M (where T is a coefficient, and Ni-1(f) is the noise spectrum one frame before the update); [006] Further comprising A noise updating circuit comprising:

2. The constant Ks is set to any value within a range corresponding to the time constant of an IIR filter or the averaging interval of an FIR filter, that is, 1 to 10 seconds.

2. The noise updating circuit according to claim 1 .

3. The coefficient Te is set to any value in the range of 1 to 100.

2. The noise updating circuit according to claim 1 .

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