Predictive Quantization of LPC Coefficients for Stereo Audio
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Solution Overview
Problem
Existing audio codecs face challenges in efficiently encoding and decoding stereo audio signals, particularly at low bit-rates, due to quantization errors in linear predictive coding (LPC) coefficients, which affect sound quality and require a balance between accuracy and computational resources.
Innovation Solution
The proposed solution involves a method for quantizing LPC filter coefficients using a predictive quantization technique that estimates and encodes coefficients for both channels of a stereo audio signal, minimizing quantization errors while optimizing bit usage and computational load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If quantization of LPC filter coefficients is performed to enable transmission from encoder to decoder, then the encoded audio signal can be transmitted at low bit-rates, but quantization error causes distortion in the reconstructed speech
Solution Approach 1:
The patent applies preliminary action by predicting the LPC coefficients for the second channel based on the quantized LPC coefficients from the first channel before actual quantization occurs. This prediction step prepares an initial estimate that reduces the subsequent quantization error, allowing for more accurate reconstruction at low bit-rates.
Solution Approach 2:
The patent implements feedback by using the quantized LPC coefficients from the first channel as input to predict the second channel's coefficients. This feedback mechanism allows the system to leverage already-processed information to improve the accuracy of subsequent processing, reducing overall quantization error while maintaining low bit-rate operation.
2Quantity of substance
If a speech production model is used to optimize speech encoding, then lower bit-rate is achieved with comparable sound quality, but music and ambient sounds are poorly represented and appear as background noise
Solution Approach 1:
The patent applies local quality by treating the two channels differently in the quantization process. The first channel undergoes direct quantization while the second channel uses predictive quantization based on the first channel's coefficients. This localized differentiation allows the system to optimize for speech-like signals in one channel while maintaining compatibility with other signal types through the predictive relationship.
3Measurement precision
If LPC encoding is used to model spectral envelope accurately for periodic signals, then speech synthesis is enabled, but the number of bits required for quantization of LP filter coefficients increases
Solution Approach 1:
The patent merges the quantization process for the second channel with the prediction process from the first channel. Instead of independently quantizing both channels' LPC coefficients, the system combines prediction based on the first channel's quantized coefficients with residual quantization, reducing the total number of bits required while maintaining spectral envelope modeling accuracy.
Data Source
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AI summary
According to an example embodiment, a technique for audio encoding is provided, the technique comprising obtaining a set of first linear prediction, LP, filter coefficients that represents a spectral envelope of an audio signal in a first channel derived from a multi-channel input audio signal; obtaining a set of second LP filter coefficients that represents a spectral envelope of an audio signal in a second channel derived from the multi-channel input audio signal; quantizing the set of first LP filter coefficients using a predefined first quantizer; and quantizing the set of second LP filter coefficients on basis of the quantized set of first LP filter coefficients, the quantization of the set of second LP filter coefficients comprising: deriving, on basis of the quantized set of first LP filter coefficients by using a predefined predictor, a set of predicted LP filter coefficients to estimate the spectral envelope of the audio signal in said second channel, computing prediction error as a difference between respective LP coefficients of the set of second LP filter coefficients and the set of predicted LP filter coefficients, and quantizing the prediction error using a predefined second quantizer.