Dual-Ended Audio Intelligence for Low-Complexity Decoder Post-Processing
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Solution Overview
Problem
Existing audio signal processing systems require significant computational complexity for content-aware processing, limiting real-time capabilities on playback devices due to the need for content analysis within the decoder.
Innovation Solution
Perform content analysis at the encoder-side and encode classification information into a bitstream, allowing the decoder to relax computational burden and enhance flexibility in audio post-processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If content analysis is performed within the decoder, then audio post-processing can be steered based on content type, but computational complexity increases significantly limiting real-time capabilities
Solution Approach 1:
The content analysis is performed in advance at the encoder side before the audio data is decoded. The encoder analyzes the audio content, determines content type classification information, and encodes this information into the bitstream. This preliminary action eliminates the need for the decoder to perform computationally intensive content analysis in real-time, thereby reducing decoder complexity while maintaining adaptability for audio post-processing steering.
2Productivity
If content analysis is performed in real-time at the playback device, then content-aware processing can be achieved, but processing speed and real-time capability are limited by affordable device capabilities
Solution Approach 1:
The encoder acts as an intermediary that performs the computationally intensive content analysis function. Instead of requiring the playback device to perform content analysis, the encoder analyzes the audio content upfront and transmits the classification information through the bitstream. This intermediary approach allows high-performance content analysis without burdening the playback device, thereby maintaining real-time processing capability on affordable devices.
3Device complexity
If classification information is transmitted in the bitstream, then decoder computational burden is reduced, but bitstream data size increases
Solution Approach 1:
The classification information is encoded using parameter-efficient representations. Instead of transmitting full spectral analysis data or detailed content descriptions, the system transmits compact classification parameters (such as content type labels and confidence scores) that convey the necessary information for audio post-processing steering with minimal data overhead, thereby reducing the increase in bitstream size.
Data Source
AI summary
A method of encoding audio content comprises performing a content analysis of the audio content, generating classification information indicative of a content type of the audio content based on the content analysis, encoding the audio content and the classification information in a bitstream, and outputting the bitstream. A method of decoding audio content from a bitstream including audio content and classification information for the audio content, wherein the classification information is indicative of a content classification of the audio content, comprises receiving the bitstream, decoding the audio content and the classification information, and selecting, based on the classification information, a post processing mode for performing post processing of the decoded audio content. Selecting the post processing mode can involve calculating one or more control weights for post processing of the decoded audio content based on the classification information.