LPC Filter Quantization Across Super-Frames at Low Bit Rates
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Solution Overview
Problem
Current speech and audio coding techniques, such as CELP, face challenges in efficiently representing LPC filters at low bit rates while maintaining subjective quality, especially in applications like multimedia streaming and broadcast, where LPC filters are quantized separately in each frame and with a fixed number of bits.
Innovation Solution
A method and device for quantizing LPC filters in a super-frame using a combination of absolute and differential quantization modes, where one filter is always quantized absolutely, and others are quantized relative to previously quantized filters, optimizing bit allocation based on correlation and distortion criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If LPC filters are quantized separately in each frame with a fixed number of bits, then the implementation is simple and straightforward, but the bit rate efficiency is poor and quality deteriorates at low bit rates
Solution Approach 1:
The patent combines multiple LPC filters from a super-frame (multiple frames) into a single quantization process. Instead of quantizing each frame's LPC filter independently, the method collects LPC filters from multiple frames, sorts them by predictability, and quantizes them together using a unified codebook search, thereby improving bit rate efficiency while maintaining implementation feasibility.
Solution Approach 2:
The patent applies differential quantization selectively to LPC filters based on their individual predictability characteristics. By sorting filters according to their predictability metrics and applying different quantization strategies (absolute vs. differential) to different filters, the method optimizes quality for each local region in the parameter space while managing overall bit rate.
2Device complexity
If LPC filters are quantized with a fixed number of bits per frame, then the bit allocation is simple, but the quality varies poorly across frames with different predictability characteristics
Solution Approach 1:
The patent introduces dynamic bit allocation within the super-frame structure. By sorting LPC filters based on their predictability and dynamically assigning different quantization methods (absolute quantization for low predictability, differential quantization for high predictability), the system adapts bit allocation to the actual characteristics of each filter, improving overall quality while keeping the allocation mechanism computationally manageable.
Solution Approach 2:
The patent changes the quantization parameter strategy by transitioning from fixed-bit quantization to variable-bit quantization based on predictability metrics. The method computes predictability measures for each LPC filter, then uses these metrics to determine the appropriate quantization approach and bit allocation, thereby optimizing quality according to actual signal characteristics.
3Loss of information
If differential quantization is used for all LPC filters, then bit rate is reduced, but error propagation increases and stability deteriorates
Solution Approach 1:
The patent segments the quantization process by dividing LPC filters into different groups based on their predictability characteristics. Filters with high predictability are processed using differential quantization to save bits, while filters with low predictability use absolute quantization to avoid error propagation. This segmentation isolates potential error sources and prevents widespread error propagation while still achieving bit rate reduction where safe.
Solution Approach 2:
The patent converts the potential harm of differential quantization (error propagation) into a benefit by using predictability metrics to identify which filters are safe for differential quantization. Filters with high predictability are selected for differential quantization because their inherent stability tolerates the quantization process, thereby transforming what could be a harmful effect into a useful bit-saving mechanism.
Data Source
AI summary
A device and a method for quantizing, in a super-frame including a sequence of frames, LPC filters calculated during the frames of the sequence. The LPC filter quantizing device and method comprises: an absolute quantizer for first quantizing one of the LPC filters using absolute quantization; and at least one quantizer of the other LPC filters using a quantization mode selected from the group consisting of absolute quantization and differential quantization relative to at least one previously quantized filter amongst the LPC filters. For inverse quantizing, at least the first quantized LPC filter is received and an inverse quantizer inverse quantizes the first quantized LPC filter using absolute inverse quantization. If any quantized LPC filter other than the first quantized LPC filter is received, an inverse quantizer inverse quantizes this quantized LPC filter using one of absolute inverse quantization and differential inverse quantization relative to at least one previously received quantized LPC filter.