Audio Encoder Bit Allocation via Frequency Sub-band Classification
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Solution Overview
Problem
Current audio encoding technologies, particularly variable bitrate (VBR) methods, do not adequately reduce the size of output data, leading to suboptimal storage and bandwidth usage.
Innovation Solution
A method for encoding audio signals by representing each audio frame in the frequency domain and classifying frequency sub-bands as background or foreground using a specific background model, allocating bits accordingly to prioritize important sounds, thereby optimizing bit allocation across different frequency sub-bands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If variable bitrate encoding is used to reduce data size, then storage space and bandwidth requirements are reduced, but the encoding complexity increases due to dynamic bitrate adjustment
Solution Approach 1:
The audio frequency spectrum is segmented into multiple frequency sub-bands, allowing independent bit allocation for each sub-band based on its characteristics and importance. This segmentation enables the encoding system to apply different compression strategies to different parts of the audio signal, reducing overall data size while maintaining quality where it matters most.
Solution Approach 2:
Different quality levels are applied to different frequency sub-bands based on their importance. Critical frequency ranges that contain important audio information are encoded with higher quality and more bits, while less important frequency ranges use lower quality and fewer bits. This local quality differentiation reduces total data size while preserving perceptual audio quality.
2Ease of manufacture
If uniform bit allocation is used across all frequency sub-bands, then encoding simplicity is maintained, but audio quality deteriorates in critical frequency ranges
Solution Approach 1:
The encoding system applies non-uniform bit allocation across frequency sub-bands, assigning more bits to critical frequency ranges and fewer bits to less important ranges. This local quality differentiation ensures high audio quality in important frequency regions while accepting lower quality in less critical regions, overall improving perceived audio quality.
Solution Approach 2:
The system dynamically changes the bit allocation parameter across different frequency sub-bands based on their characteristics. By adjusting the number of bits allocated to each sub-band according to its importance and content, the system optimizes audio quality while efficiently using the available bitrate.
Data Source
AI summary
A method, a computer program product, an encoder and a monitoring device for encoding an audio signal with variable bitrate, wherein: an audio signal comprising a plurality of successive audio frames is received; and for each successive audio frame of the audio signal: the audio frame is represented in a frequency domain with respect to a plurality of frequency sub-bands; the audio frame is classified in each frequency sub-band as either background or foreground using a background model specific to the frequency sub-band; each successive audio frame of the audio signal is encoded, wherein a number of bits is allocated for each frequency sub-band of the audio frame, wherein the number of bits allocated for a frequency sub-band is higher if the audio frame is classified as foreground in the frequency sub-band than if the audio frame is classified as background in the frequency sub-band.