Audio Encoder Asymmetric Windowing Low Delay Mode Switching
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Solution Overview
Problem
Existing audio coding technologies face challenges in achieving a good tradeoff between bitrate efficiency, audio quality, and low encoding and decoding delay, especially when switching between different coding modes, as they often result in noticeable delays and bitrate overheads.
Innovation Solution
The implementation of a multimode audio coding system that uses a transform-domain path and a code-excited linear-prediction-domain path, with a predetermined asymmetric analysis and synthesis window, allowing for efficient windowing and aliasing cancellation information to maintain coding efficiency and audio quality while minimizing delay.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If mode switching is implemented to adapt to different audio content, then coding efficiency is improved, but encoding and decoding delay increases
Solution Approach 1:
The encoder performs preliminary analysis of the audio content to predict the optimal coding mode in advance. By analyzing characteristics such as signal energy, zero-crossing rate, and spectral flatness before actual encoding, the system can prepare mode switching decisions proactively, reducing the delay caused by real-time mode analysis during encoding.
Solution Approach 2:
The coding mode is made dynamic and adaptable rather than fixed. The system continuously monitors audio content characteristics and dynamically switches between different coding modes (e.g., transform coding, ACELP, mixed coding) to optimize performance for different signal types while maintaining low latency through efficient mode transition mechanisms.
2Productivity
If mode switching is implemented to adapt to different audio content, then coding efficiency is improved, but bitrate overhead increases
Solution Approach 1:
The system changes coding parameters dynamically based on audio content characteristics. By adjusting parameters such as frame size, transform type, and excitation model according to the signal properties, the encoder achieves high coding efficiency without requiring excessive bitrate for mode signaling. The parameter changes are optimized to minimize overhead while maximizing performance.
Solution Approach 2:
Different coding modes and parameter sets are applied locally to different segments of audio content based on their specific characteristics. Rather than using a single global mode, the system applies transform coding for tonal segments, ACELP for speech-like segments, and mixed coding for transitions, optimizing each local segment while minimizing overall bitrate overhead through efficient mode selection.
3Manufacturing precision
If mode switching is implemented to adapt to different audio content, then audio quality is improved, but encoding and decoding delay increases
Solution Approach 1:
The system performs preliminary quality assessment and mode selection based on audio content analysis before encoding. By pre-determining the optimal coding mode for each segment based on characteristics like signal energy, zero-crossing rate, and spectral flatness, the system ensures high audio quality while minimizing the delay introduced by mode switching decisions.
Solution Approach 2:
The coding system dynamically adapts to different audio content types by switching between transform coding for high-quality music segments, ACELP for speech segments, and mixed coding for transitions. This dynamic adaptation maintains high audio quality across different content types while using efficient mode transition mechanisms to minimize encoding and decoding delay.
Data Source
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AI summary
An audio signal encoder (100) comprises a transform-domain path (12) configured to obtain a set of spectral coefficients (124) and noise-shaping information (126) on the basis of a time-domain representation (122) of a portion of the audio content to be encoded in a transform-domain mode. The transform-domain path comprises a time-domain-to-frequency-domain converter (130) configured to window a time-domain representation of the audio content, or a pre-processed version thereof, to obtain a windowed representation of the audio content, and to apply a time-domain-to-frequency-domain conversion, to derive a set of spectral coefficients from the windowed time-domain representation of the audio content. The audio signal decoder comprises a CELP path (140) configured to obtain an code-excitation information (144) and a linear-prediction-domain parameter information (146) on the basis of a portion of the audio content to be encoded in a CELP mode. The time-domain-to-frequency-domain converter (136) is configured to apply a predetermined asymmetric analysis window (520) for a windowing of a current portion of the audio content to be encoded in the transform-domain mode and following a portion of the audio content encoded in the transform-domain mode both if the current portion of the audio content is followed by a subsequent portion of the audio content to be encoded in the transform-domain mode and if the current portion of the audio content is followed by a subsequent portion of the audio content to be encoded in the CELP mode. The audio signal encoder is configured to selectively provide an aliasing cancellation information (164) if the current portion of the audio content is followed by a subsequent portion of the audio content to be encoded in the CELP mode.