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Speech quality evaluation of a sparse coding shrinkage noise reduction algorithm with normal hearing and hearing
Jinqiu Sang1, Hongmei Hu2, Chengshi Zheng3
1Institute of Sound and Vibration Research, University of Southampton, SO17 1BJ, UK; Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China.
Hearing Research
|August 2, 2015
Summary
A new sparse coding shrinkage (SCS) algorithm shows promise for hearing aid noise reduction. While effective, it introduces distortions perceived by normal-hearing listeners but not by those with hearing impairments.
Area of Science:
- Audiology
- Signal Processing
- Speech Technology
Background:
- Limited research comprehensively evaluates noise reduction algorithms' impact on speech quality for hearing-impaired (HI) individuals.
- Existing studies often focus on speech intelligibility, neglecting subjective quality assessments.
- A model-based sparse coding shrinkage (SCS) algorithm has demonstrated competitive speech intelligibility compared to traditional Wiener filters.
Purpose of the Study:
- To comprehensively evaluate the effects of noise reduction algorithms on speech quality for HI listeners.
- To quantitatively link speech intelligibility benefits with speech quality using the Interpolated Paired Comparison Rating (IPCR) method.
- To compare the performance of the SCS algorithm against a Wiener filter in terms of subjective speech quality and objective measures.
Main Methods:
- Subjective speech quality tests were conducted using the Interpolated Paired Comparison Rating (IPCR) method.
- Objective measures including frequency-weighted segmental signal-to-noise ratio (fwsegSNR), perceptual evaluation of speech quality (PESQ), and hearing aid speech quality index (HASQI) were employed.
- Comparisons were made between the SCS algorithm, a Wiener filter, and listener groups including hearing-impaired (HI) and normal-hearing (NH) individuals.
Main Results:
- Little difference in speech quality was observed between the SCS and Wiener filter algorithms for HI listeners.
- HI listeners generally provided better quality ratings for noise reduction algorithms than NH listeners.
- The SCS algorithm reduced noise more efficiently but introduced higher distortions, which were detected by NH listeners but not by HI listeners.
Conclusions:
- The SCS algorithm is a promising candidate for noise reduction in hearing aids, offering efficient noise reduction.
- Care must be taken when adapting algorithms developed for NH listeners to hearing aid applications for HI individuals.
- Algorithms evaluated negatively by NH listeners may still offer significant benefits to HI users.
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