Audio Encoder Block Switching for Pre-Echo Suppression
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Solution Overview
Problem
Existing audio codec technologies fail to effectively control or eliminate pre-echo artifacts, particularly noticeable in audio with sharp impulses and transient signals, due to inaccuracies during time domain to frequency domain transformation and back, leading to suboptimal sound quality in dynamic and distributed IP-based multimedia systems.
Innovation Solution
A computer-implemented system and method that encodes sampled audio signals by identifying potential pre-echo events, generating an error signal, and encoding this information into a bitstream, allowing for the removal of pre-echo artifacts during decoding, using techniques such as pulse code modulation, adaptive pulse code modulation, and modified discrete cosine transform.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If MDCT transform is used to convert time domain signal to frequency domain and back, then audio compression is achieved, but pre-echo artifacts are introduced due to error spreading across block size
Solution Approach 1:
The audio signal is divided into multiple blocks for MDCT processing, and the patent identifies specific blocks containing transient signals. By segmenting the processing approach - using different block sizes (short blocks for transients, long blocks for steady-state signals) and applying pre-echo suppression specifically to identified transient blocks, the system maintains compression efficiency while eliminating pre-echo artifacts in critical regions.
Solution Approach 2:
The patent applies pre-echo suppression selectively rather than uniformly across the entire audio signal. By detecting transient signals and applying suppression only to blocks containing these transients, the system maintains high audio quality where needed while preserving compression efficiency in non-critical regions. The suppression strength and block size are adapted locally based on signal characteristics.
2Quantity of substance
If quantization is applied during MDCT encoding, then bit rate reduction is achieved, but audio quality deteriorates due to quantization errors
Solution Approach 1:
The patent employs adaptive quantization where quantization parameters are dynamically adjusted based on signal characteristics. For blocks containing transient signals, finer quantization is applied to preserve audio quality, while for steady-state blocks, coarser quantization is used to achieve lower bit rates. This dynamic adaptation allows the system to optimize the trade-off between bit rate and audio quality for different signal regions.
Solution Approach 2:
The system changes quantization parameters (such as quantization step size and precision) based on the detected signal type. When transients are detected, the quantization precision is increased for those specific blocks to prevent quality degradation, while maintaining lower precision for other blocks to achieve overall bit rate reduction. This parameter adaptation resolves the contradiction between compression and quality.
3Device complexity
If fixed block size MDCT is used for encoding, then encoding simplicity is maintained, but pre-echo cannot be effectively controlled for transient signals
Solution Approach 1:
The patent performs preliminary analysis of the audio signal to detect transient blocks before applying MDCT encoding. By identifying transient signals in advance, the system can prepare appropriate block sizes and suppression parameters for these blocks, allowing effective pre-echo control without significantly increasing overall encoding complexity. The preliminary detection enables targeted processing only where needed.
Solution Approach 2:
The system transitions from fixed block size to dynamic block size selection based on signal content. When transients are detected, shorter block sizes are used for those specific blocks to reduce pre-echo, while longer blocks are used for steady-state signals to maintain compression efficiency. This dynamic block size adaptation effectively controls pre-echo without requiring completely complex encoding structures.
Data Source
AI summary
An encoder operable to filter audio signals into a plurality of frequency band components, generate quantized digital components for each band, identify a potential for pre-echo events within the generated quantized digital components, generate an approximate signal by decoding the quantized digital components using inverse pulse code modulation, generate an error signal by comparing the approximate signal with the sampled audio signal, and process the error signal and quantized digital components. The encoder operable to process the error signal by processing delayed audio signals and Q band values, determining the potential for pre-echo events from the Q band values, and determining scale factors and MDCT block sizes for the potential for pre-echo events. The encoder operable to transform the error signal into high resolution frequency components using the MDCT block sizes, quantize the scale factors and frequency components, and encode the quantized lines, block sizes, and quantized scale factors for inclusion in the bitstream.