scholarly journals Speech intelligibility enhancement for Thai-speaking cochlear implant listeners

2019 ◽  
Vol 13 (3) ◽  
pp. 866
Author(s):  
Siriporn Dachasilaruk ◽  
Niphat Jantharamin ◽  
Apichai Rungruang
Keyword(s):  
Cochlear Implant ◽  
Speech Enhancement ◽  
Speech Intelligibility ◽  
English Language ◽  
Single Channel ◽  
Spectral Subtraction ◽  
Monosyllabic Words ◽  
Listening Environments ◽  
Babble Noise ◽  
Vocoded Speech

Cochlear implant (CI) listeners encounter difficulties in communicating with other persons in noisy listening environments. However, most CI research has been carried out using the English language. In this study, single-channel speech enhancement (SE) strategies as a pre-processing approach for the CI system were investigated in terms of Thai speech intelligibility improvement. Two SE algorithms, namely multi-band spectral subtraction (MBSS) and Weiner filter (WF) algorithms, were evaluated. Speech signals consisting of monosyllabic and bisyllabic Thai words were degraded by speech-shaped noise and babble noise at SNR levels of 0, 5, and 10 dB. Then the noisy words were enhanced using SE algorithms. The enhanced words were fed into the CI system to synthesize vocoded speech. The vocoded speech was presented to twenty normal-hearing listeners. The results indicated that speech intelligibility was marginally improved by the MBSS algorithm and significantly improved by the WF algorithm in some conditions. The enhanced bisyllabic words showed a noticeably higher intelligibility improvement than the enhanced monosyllabic words in all conditions, particularly in speech-shaped noise. Such outcomes may be beneficial to Thai-speaking CI listeners.

Perceptual Learning of Vocoded Speech With and Without Contralateral Hearing: Implications for Cochlear Implant Rehabilitation

2020 ◽  
pp. 1-10
Author(s):  
Martin Chavant ◽  
Alexis Hervais-Adelman ◽  
Olivier Macherey
Keyword(s):  
Cochlear Implant ◽  
Perceptual Learning ◽  
Speech Signal ◽  
Training Phase ◽  
Monosyllabic Words ◽  
Low Pass ◽  
Contralateral Ear ◽  
Number Of Individuals ◽  
Insight Into ◽  
Vocoded Speech

Purpose An increasing number of individuals with residual or even normal contralateral hearing are being considered for cochlear implantation. It remains unknown whether the presence of contralateral hearing is beneficial or detrimental to their perceptual learning of cochlear implant (CI)–processed speech. The aim of this experiment was to provide a first insight into this question using acoustic simulations of CI processing. Method Sixty normal-hearing listeners took part in an auditory perceptual learning experiment. Each subject was randomly assigned to one of three groups of 20 referred to as NORMAL, LOWPASS, and NOTHING. The experiment consisted of two test phases separated by a training phase. In the test phases, all subjects were tested on recognition of monosyllabic words passed through a six-channel “PSHC” vocoder presented to a single ear. In the training phase, which consisted of listening to a 25-min audio book, all subjects were also presented with the same vocoded speech in one ear but the signal they received in their other ear differed across groups. The NORMAL group was presented with the unprocessed speech signal, the LOWPASS group with a low-pass filtered version of the speech signal, and the NOTHING group with no sound at all. Results The improvement in speech scores following training was significantly smaller for the NORMAL than for the LOWPASS and NOTHING groups. Conclusions This study suggests that the presentation of normal speech in the contralateral ear reduces or slows down perceptual learning of vocoded speech but that an unintelligible low-pass filtered contralateral signal does not have this effect. Potential implications for the rehabilitation of CI patients with partial or full contralateral hearing are discussed.

Dual-channel spectral subtraction algorithms based speech enhancement dedicated to a bilateral cochlear implant

2012 ◽  
Vol 73 (1) ◽  
pp. 12-20 ◽  
Author(s):  
Fathi Kallel ◽  
Mondher Frikha ◽  
Mohamed Ghorbel ◽  
Ahmed Ben Hamida ◽  
Christian Berger-Vachon
Keyword(s):  
Cochlear Implant ◽  
Speech Enhancement ◽  
Spectral Subtraction ◽  
Dual Channel ◽  
Bilateral Cochlear Implant

scholarly journals Noise reduction in hearing aids using spectral subtraction techniques

2021 ◽  
Author(s):  
Fatos Myftari
Keyword(s):  
Noise Reduction ◽  
Hearing Aids ◽  
Speech Intelligibility ◽  
Single Channel ◽  
Subjective Evaluation ◽  
Hearing Impaired ◽  
Spectral Subtraction ◽  
Reduction Algorithm ◽  
Subjective Testing ◽  
Noise Reduction Algorithm

This thesis is concerned with noise reduction in hearing aids. Hearing - impaired listeners and hearing - impaired users have great difficulty understanding speech in a noisy background. This problem has motivated the development and the use of noise reduction algorithms to improve the speech intelligibility in hearing aids. In this thesis, two noise reduction algorithms for single channel hearing instruments are presented, evaluated using objective and subjective tests. The first noise reduction algorithm, conventional Spectral Subtraction, is simulated using MATLAB 6.5, R13. The second noise reduction algorithm, Spectral Subtraction in wavelet domanin is introduced as well. This algorithm is implemented off line, and is compared with conventional Spectral Subtraction. A subjective evaluation demonstrates that the second algorithm has additional advantages in speech intelligibility, in poor listening conditions relative to conventional Spectral Subtraction. The subjective testing was performed with normal hearing listeners, at Ryerson University. The objective evaluation shows that the Spectral Subtraction in wavelet domain has improved Signal to Noise Ratio compared to conventional Spectral Subtraction.

scholarly journals Speech enhancement based on neural networks improves speech intelligibility in noise for cochlear implant users

2017 ◽  
Vol 344 ◽  
pp. 183-194 ◽  
Author(s):  
Tobias Goehring ◽  
Federico Bolner ◽  
Jessica J.M. Monaghan ◽  
Bas van Dijk ◽  
Andrzej Zarowski ◽  
...  
Keyword(s):  
Neural Networks ◽  
Cochlear Implant ◽  
Speech Enhancement ◽  
Speech Intelligibility

Speech enhancement based on perceptually motivated guided spectrogram filtering

2021 ◽  
pp. 1-12
Author(s):  
Jie Wang ◽  
Linhuang Yan ◽  
Qiaohe Yang ◽  
Minmin Yuan
Keyword(s):  
Auditory System ◽  
Speech Enhancement ◽  
Speech Intelligibility ◽  
Single Channel ◽  
Noisy Environments ◽  
Human Auditory System ◽  
Residual Noise ◽  
Guided Filtering ◽  
Degraded Image ◽  
Linear Transform

In this paper, a single-channel speech enhancement algorithm is proposed by using guided spectrogram filtering based on masking properties of human auditory system when considering a speech spectrogram as an image. Guided filtering is capable of sharpening details and estimating unwanted textures or background noise from the noisy speech spectrogram. If we consider the noisy spectrogram as a degraded image, we can estimate the spectrogram of the clean speech signal using guided filtering after subtracting noise components. Combined with masking properties of human auditory system, the proposed algorithm adaptively adjusts and reduces the residual noise of the enhanced speech spectrogram according to the corresponding masking threshold. Because the filtering output is a local linear transform of the guidance spectrogram, the local mask window slides can be efficiently implemented via box filter with O(N) computational complexity. Experimental results show that the proposed algorithm can effectively suppress noise in different noisy environments and thus can greatly improve speech quality and speech intelligibility.

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