Analysis of compressive properties of the BioAid hearing aid algorithm

Combination and Comparison of Sound Coding Strategies Using Cochlear Implant Simulation With Mandarin Speech

Three cochlear implant (CI) sound coding strategies were combined in the same signal processing path and compared for speech intelligibility with vocoded Mandarin sentences. The three CI coding strategies, biologically-inspired hearing aid algorithm (BioAid), envelope enhancement (EE), and fundamental frequency modulation (F0mod), were combined with the advanced combination encoder (ACE) strategy. Hence, four singular coding strategies and four combinational coding strategies were derived. Mandarin sentences with speech-shape noise were processed using these coding strategies. Speech understanding of vocoded Mandarin sentences was evaluated using short-time objective intelligibility (STOI) and subjective sentence recognition tests with normal-hearing listeners. For signal-to-noise ratios at 5 dB or above, the EE strategy had slightly higher average scores in both STOI and listening tests compared to ACE. The addition of EE to BioAid slightly increased the mean scores for BioAid+EE, which was the combination strategy with the highest scores in both objective and subjective speech intelligibility. The benefits of BioAid, F0mod, and the four combinational coding strategies were not observed in CI simulation. The findings of this study may be useful for the future design of coding strategies and related studies with Mandarin.

Adaptation to Noise in Human Speech Recognition Depends on Noise-Level Statistics and Fast Dynamic-Range Compression

Human hearing adapts to background noise, as evidenced by the fact that listeners recognize more isolated words when words are presented later rather than earlier in noise. This adaptation likely occurs because the leading noise shifts ("adapts") the dynamic range of auditory neurons, which can improve the neural encoding of speech spectral and temporal cues. Because neural dynamic range adaptation depends on stimulus-level statistics, here we investigated the importance of "statistical" adaptation for improving speech recognition in noisy backgrounds. We compared the recognition of noised-masked words in the presence and in the absence of adapting noise precursors whose level was either constant or was changing every 50 ms according to different statistical distributions. Adaptation was measured for 28 listeners (9 men) and was quantified as the recognition improvement in the precursor relative to the no-precursor condition. Adaptation was largest for constant-level precursors and did not occur for highly fluctuating precursors, even when the two types of precursors had the same mean level and both activated the medial olivocochlear reflex. Instantaneous amplitude compression of the highly fluctuating precursor produced as much adaptation as the constant-level precursor did without compression. Together, results suggest that noise adaptation in speech recognition is probably mediated by neural dynamic range adaptation to the most frequent sound level. Further, they suggest that auditory peripheral compression per se, rather than the medial olivocochlear reflex, could facilitate noise adaptation by reducing the level fluctuations in the noise.SIGNIFICANCE STATEMENT Recognizing speech in noise is challenging but can be facilitated by noise adaptation. The neural mechanisms underlying this adaptation remain unclear. Here, we report some benefits of adaptation for word-in-noise recognition and show that (1) adaptation occurs for stationary but not for highly fluctuating precursors with equal mean level; (2) both stationary and highly fluctuating noises activate the medial olivocochlear reflex; and (3) adaptation occurs even for highly fluctuating precursors when the stimuli are passed through a fast amplitude compressor. These findings suggest that noise adaptation reflects neural dynamic range adaptation to the most frequent noise level and that auditory peripheral compression, rather than the medial olivocochlear reflex, could facilitate noise adaptation.

Binaural model-based dynamic-range compression

OBJECTIVE

Binaural cues such as interaural level differences (ILDs) are used to organise auditory perception and to segregate sound sources in complex acoustical environments. In bilaterally fitted hearing aids, dynamic-range compression operating independently at each ear potentially alters these ILDs, thus distorting binaural perception and sound source segregation.

DESIGN

A binaurally-linked model-based fast-acting dynamic compression algorithm designed to approximate the normal-hearing basilar membrane (BM) input-output function in hearing-impaired listeners is suggested. A multi-center evaluation in comparison with an alternative binaural and two bilateral fittings was performed to assess the effect of binaural synchronisation on (a) speech intelligibility and (b) perceived quality in realistic conditions.

STUDY SAMPLE

30 and 12 hearing impaired (HI) listeners were aided individually with the algorithms for both experimental parts, respectively.

RESULTS

A small preference towards the proposed model-based algorithm in the direct quality comparison was found. However, no benefit of binaural-synchronisation regarding speech intelligibility was found, suggesting a dominant role of the better ear in all experimental conditions.

CONCLUSION

The suggested binaural synchronisation of compression algorithms showed a limited effect on the tested outcome measures, however, linking could be situationally beneficial to preserve a natural binaural perception of the acoustical environment.