Adaptive Audio Companding for Dense Transient Noise Reduction
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Solution Overview
Problem
Existing audio processing techniques struggle to effectively reduce quantization noise, particularly in transient signals like applause, fire crackling, or rain, due to the difficulty in predicting the appropriate companding technique based on signal content.
Innovation Solution
A signal-dependent companding system that adapts companding based on detected signal content, using a detector to differentiate between speech, applause, and tonal audio content, and applying appropriate companding exponents to improve sound quality for dense transient signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If companding is applied to reduce quantization noise, then sound quality is improved, but it is difficult to predict the appropriate companding technique for different signal types
Solution Approach 1:
The system changes the companding exponent parameter based on the detected signal type. Different exponent values are applied for speech, applause, and tonal audio content to optimize noise reduction for each signal category while maintaining audio quality.
Solution Approach 2:
The system uses a detector to analyze the input signal and provides feedback about the signal type to the companding module. This feedback mechanism enables adaptive selection of companding parameters based on the actual signal characteristics.
2Measurement precision
If a detector is designed to differentiate between speech, applause, and tonal audio content, then companding accuracy is improved, but device complexity increases
Solution Approach 1:
The detector is designed to segment the audio signal into distinct categories (speech, applause, tonal content) based on specific characteristics. This segmentation approach allows for simplified detection rules for each category rather than attempting to analyze all possible signal variations simultaneously.
Solution Approach 2:
The system applies different detection criteria and companding parameters for different signal types. Each signal category has its own optimized detection approach and corresponding companding exponent, allowing for accurate classification without requiring a single complex universal detector.
3Quantity of substance
If lossy data compression is applied to reduce storage requirements, then data rate is reduced, but quantization noise is introduced
Solution Approach 1:
The system converts the harmful quantization noise introduced by lossy compression into a beneficial effect by using companding to reshape the noise spectrum. The companding process reduces the perceptibility of quantization noise by adjusting the dynamic range, thereby improving perceived audio quality despite the presence of compression artifacts.
Data Source
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Figure 3A
AI summary
Embodiments are directed to a companding method and system for reducing coding noise in an audio codec. A method of processing an audio signal includes the following operations. A system receives an audio signal. The system determines that a first frame of the audio signal includes a sparse transient signal. The system determines that a second frame of the audio signal includes a dense transient signal. The system compresses/expands (compands) the audio signal using a companding rule that applies a first companding exponent to the first frame of the audio signal and applies a second companding exponent to the second frame of the audio signal, each companding exponent being used to derive a respective degree of dynamic range compression and expansion for a corresponding frame. The system then provides the companded audio signal to a downstream device.