Adaptive ADPCM Quantization Using Short- and Long-Period Signal Changes
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Solution Overview
Problem
Conventional ADPCM techniques face limitations in further compressing data while maintaining sound quality, as they do not effectively adapt quantization rates based on signal changes, leading to suboptimal compression and potential degradation in sound reproduction.
Innovation Solution
The proposed ADPCM encoding and decoding apparatuses incorporate high-frequency and low-frequency measuring sections to detect short-period and long-period changes in PCM signals, allowing for adaptive quantization and inverse-quantization, which dynamically adjust the quantization rate based on these changes, thereby optimizing compression and sound quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If conventional ADPCM encoding is used to compress data, then data compression is achieved, but sound quality degrades
Solution Approach 1:
The patent applies dynamics by making the quantization width variable rather than fixed. The quantization width is dynamically adjusted based on the absolute value of the differential value and the decoded signal value, allowing the system to adapt to different signal conditions and maintain sound quality while achieving compression
Solution Approach 2:
The patent changes the parameter of quantization width from a fixed value to a variable value that depends on signal characteristics. By changing this parameter dynamically based on the differential value and decoded signal, the system optimizes both compression efficiency and sound quality
2Device complexity
If fixed quantization width is used in ADPCM, then encoding simplicity is maintained, but compression efficiency and sound quality are suboptimal
Solution Approach 1:
The patent introduces parameter changes by making the quantization width variable based on signal characteristics. This allows the system to improve compression efficiency without requiring complex adaptive algorithms, maintaining relative encoding simplicity while achieving better performance
3Quantity of substance
If adaptive quantization based on differential value alone is used, then some compression optimization is achieved, but sound quality still degrades under certain conditions
Solution Approach 1:
The patent applies local quality by making the quantization width dependent on both the differential value and the decoded signal value. This localized adaptation to different signal conditions ensures that quantization quality is optimized for each specific signal state, preventing sound quality degradation
Solution Approach 2:
The patent uses feedback by incorporating the decoded signal value into the quantization width determination. The decoded signal from previous samples provides feedback that helps adjust the quantization width to maintain sound quality while achieving compression
Data Source
AI summary
A signal corresponding to a short-period change and a signal corresponding to a long-period change of a sound signal are detected, and optimal quantization is performed based on the combination, of the two signals. In an ADPCM encoding apparatus (100), a differential value dn between a 16-bit input signal Xn and a decoded signal Yn-1 of one sample ago is calculated by a subtractor (102). Thereafter, the 16-bit differential value dn is adaptively quantized by an adaptive quantizing section (103), so as to be converted to a (1 to 8)-bit length-variable ADPCM value Dn. Thereafter, the ADPCM value Dn is compression-encoded by a compression-encoding section (108) to generate a signal D'n, and the signal D'n is framed by a framing section (130) and outputted. Further, in an ADPCM decoding apparatus, a framed input signal is subjected to a reverse of the aforesaid process so as to be decoded.