Parallel Music Classifier for Hearing Aids
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Solution Overview
Problem
Hearing aids face challenges in automating audio adjustments to provide a natural experience without significantly increasing power consumption or size, as detecting environment and audio types is computationally complex and power-intensive.
Innovation Solution
A computationally efficient music classifier is developed for audio devices, using a signal conditioning unit to transform audio signals into frequency bands, with parallel decision-making units detecting music characteristics like beats and tones, and a combination unit determining music presence by weighting and combining feature scores, which can be implemented in hearing aids to adjust audio processing accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If automated audio detection and classification is implemented in hearing aids, then the natural experience and audio adjustment capability are improved, but power consumption increases
Solution Approach 1:
The audio signal is divided into multiple frequency bands (e.g., 8 bands from 60-8000 Hz), and separate detection units process each band independently. This segmentation allows parallel processing with reduced computational complexity compared to analyzing the full spectrum sequentially, thereby reducing power consumption while maintaining detection accuracy.
Solution Approach 2:
The system performs partial analysis by focusing only on specific frequency bands that are most relevant for music detection, rather than processing the entire audio spectrum. The beat detection unit and tone detection unit selectively analyze portions of the signal, reducing overall computational load and power consumption.
2Adaptability or versatility
If the number of detectable environment types and audio types is increased, then the natural experience is improved, but power consumption increases further
Solution Approach 1:
The music classifier is designed to detect multiple audio characteristics (beats, tones, modulation) across multiple frequency bands simultaneously using a unified architecture. The same parallel detection units process different frequency bands, providing versatile music detection capability without requiring separate dedicated systems for each detection task, thus avoiding proportional increases in power consumption.
3Measurement precision
If complex music detection algorithms are used, then detection accuracy is improved, but computational complexity increases
Solution Approach 1:
The detection system is segmented into specialized units: a beat detection unit that analyzes rhythmic patterns, a tone detection unit that identifies pitch characteristics, and a modulation detection unit that captures temporal variations. Each unit focuses on specific acoustic features, achieving comprehensive music detection accuracy through divided functionality rather than a single complex algorithm.
Solution Approach 2:
The system applies detection algorithms selectively to only those frequency bands and audio characteristics that are most indicative of music presence. Rather than applying full-complexity analysis to the entire signal, the system performs targeted partial analysis on relevant portions, maintaining high detection accuracy while reducing overall computational complexity.
Data Source
AI summary
An audio device that includes a music classifier that determines when music is present in an audio signal is disclosed. The audio device is configured to receive audio, process the received audio, and to output the processed audio to a user. The processing may be adjusted based on the output of the music classifier. The music classifier utilizes a plurality of decision making units, each operating on the received audio independently. The decision making units are simplified to reduce the processing, and therefore the power, necessary for operation. Accordingly each decision making unit may be insufficient to determine music alone but in combination may accurately detect music while consuming power at a rate that is suitable for a mobile device, such as a hearing aid.