Integrated Speech and Audio Decoding by Signal Analysis
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Solution Overview
Problem
Existing speech and audio codecs operate independently, failing to effectively encode and decode signals based on their unique characteristics, necessitating a technology that can selectively use internal modules to optimize encoding and decoding for both speech and audio signals.
Innovation Solution
A method and apparatus that integrate speech and audio encoding and decoding by analyzing signal characteristics to select appropriate internal modules, such as conversion encoders and decoders, to enhance sound quality at various bitrates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If speech and audio codecs operate independently, then each codec can be optimized for its specific signal type, but the system cannot effectively adapt to mixed speech-audio signals
Solution Approach 1:
The integrated codec is designed to handle multiple signal types (pure speech, pure audio, and mixed speech-audio signals) through a unified structure that incorporates both speech coding modules (CELP, ACELP) and audio coding modules (MDCT, psychoacoustic modeling). The system universally processes all signal types by dynamically selecting and combining appropriate modules based on signal characteristics.
Solution Approach 2:
The codec dynamically adjusts its operation mode by analyzing signal characteristics in real-time. The speech/audio signal determination unit continuously evaluates the input signal and dynamically switches between different coding strategies (speech-oriented, audio-oriented, or hybrid modes), making the system adaptable to changing signal conditions without requiring separate fixed codecs.
2Device complexity
If a unified codec structure is used for both speech and audio, then device complexity is reduced, but encoding and decoding performance for specific signal types deteriorates
Solution Approach 1:
The unified codec is segmented into distinct functional modules: speech parameter extraction units (LPC analysis, pitch detection), audio processing units (MDCT transformation, psychoacoustic analysis), and a control unit that orchestrates module selection. This segmentation allows each module to be optimized for its specific function while maintaining overall system integration, ensuring high encoding precision for both speech and audio signals.
Solution Approach 2:
Different parts of the codec are designed with specialized quality characteristics: the speech coding path uses parameters optimized for human speech (formants, pitch), while the audio coding path uses parameters optimized for general audio (frequency domain representation, masking thresholds). The system applies the appropriate local quality characteristics automatically based on the detected signal type, maintaining high encoding precision regardless of signal content.
3Reliability
If internal modules are not selectively activated, then processing speed is maintained, but sound quality at various bitrates deteriorates
Solution Approach 1:
The codec performs self-analysis of the input signal characteristics and automatically determines the appropriate coding mode without external intervention. The speech/audio signal determination unit self-evaluates the signal and triggers the corresponding processing pipeline, enabling the system to maintain high sound quality by selecting optimal encoding parameters while preserving processing efficiency through automated decision-making.
Solution Approach 2:
The system incorporates feedback loops where the output of signal analysis feeds into mode selection, which then determines the encoding parameters. The decoded signal quality is implicitly monitored through the encoding process, and adjustments are made automatically to maintain optimal sound quality at different bitrates based on the detected signal characteristics.
Data Source
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AI summary
Provided are an apparatus and a method for integrally encoding and decoding a speech signal and a audio signal. The encoding apparatus may include: an input signal analyzer to analyze a characteristic of an input signal; a first conversion encoder to convert the input signal to a frequency domain signal, and to encode the input signal when the input signal is a audio characteristic signal; a Linear Predictive Coding (LPC) encoder to perform LPC encoding of the input signal when the input signal is a speech characteristic signal; and a bitstream generator to generate a bitstream using an output signal of the first conversion encoder and an output signal of the LPC encoder.