Adaptive Audio Encoding Mode Selection
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Solution Overview
Problem
Conventional voice/music compression algorithms, such as AMR-WB plus, compromise on sound quality or compression rate when compressing audio signals, as they either use time-based encoding for voice signals or frequency-based encoding for audio signals, leading to inferior output quality compared to voice or audio codecs respectively.
Innovation Solution
An adaptive time/frequency-based audio encoding and decoding method that divides input audio data into frequency-domain signals, selecting either time-based or frequency-based encoding modes for each signal based on spectral tilt, signal energy, and voicing levels, using techniques like frequency-varying modulated lapped transform, code excited linear prediction, and psychoacoustic modeling to optimize encoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If time-based encoding is used for voice signals, then voice compression efficiency is improved, but sound quality deteriorates
Solution Approach 1:
The audio signal is divided into multiple frequency bands using a frequency-domain transform. Each band is then independently encoded using either time-based or frequency-based encoding, allowing optimization for different signal characteristics while maintaining overall sound quality
Solution Approach 2:
The encoding mode (time-based or frequency-based) is dynamically selected for each frequency band based on signal characteristics such as spectral tilt, signal energy, and voicing level. This adaptive approach allows the system to optimize compression efficiency while maintaining sound quality across varying signal conditions
2Productivity
If frequency-based encoding is used for audio signals, then audio compression efficiency is improved, but sound quality deteriorates
Solution Approach 1:
The audio signal is segmented into multiple frequency bands, with each band independently encoded. This allows frequency-based encoding to be applied only where appropriate while preserving sound quality in bands where it is less effective
Solution Approach 2:
Different encoding methods are applied to different frequency bands based on their local characteristics. Bands with characteristics suitable for frequency-based encoding receive that treatment, while other bands use time-based encoding, optimizing overall sound quality while maintaining compression efficiency
3Device complexity
If a single encoding mode is used for all frequency bands, then device complexity is reduced, but compression efficiency deteriorates
Solution Approach 1:
The system dynamically selects between time-based and frequency-based encoding modes for each frequency band based on signal characteristics. This adaptive approach improves compression efficiency without requiring a completely separate encoding system, as the same encoder can switch modes as needed
Solution Approach 2:
The encoding parameters (specifically the encoding mode) are changed based on signal characteristics such as spectral tilt, signal energy, and voicing level. This allows the system to optimize compression efficiency for different signal conditions while using a single flexible encoding apparatus
Data Source
AI summary
Adaptive time/frequency-based audio encoding and decoding apparatuses and methods. The encoding apparatus includes a transformation & mode determination unit to divide an input audio signal into a plurality of frequency-domain signals and to select a time-based encoding mode or a frequency-based encoding mode for each respective frequency-domain signal, an encoding unit to encode each frequency-domain signal in the respective encoding mode, and a bitstream output unit to output encoded data, division information, and encoding mode information for each respective frequency-domain signal. In the apparatuses and methods, acoustic characteristics and a voicing model are simultaneously applied to a frame, which is an audio compression processing unit. As a result, a compression method effective for both music and voice can be produced, and the compression method can be used for mobile terminals that require audio compression at a low bit rate.