Speech enhancement based on neural networks applied to cochlear implant coding strategies

Federico Bolner*, Tobias Goehring, Jessica Monaghan, Bas Van Dijk, Jan Wouters, Stefan Bleeck

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

13 Citations (Scopus)

Abstract

Traditionally, algorithms that attempt to significantly improve speech intelligibility in noise for cochlear implant (CI) users have met with limited success, particularly in the presence of a fluctuating masker. In the present study, a speech enhancement algorithm integrating an artificial neural network (NN) into CI coding strategies is proposed. The algorithm decomposes the noisy input signal into time-frequency units, extracts a set of auditory-inspired features and feeds them to the NN to produce an estimation of which CI channels contain more perceptually important information (higher signal-to-noise ratio, SNR). This estimate is then used accordingly to retain a subset of channels for electrical stimulation, as in traditional n-of-m coding strategies. The proposed algorithm was tested with 10 normal-hearing participants listening to CI noise-vocoder simulations against a conventional Wiener filter based enhancement algorithm. Significant improvements in speech intelligibility in stationary and fluctuating noise were found over both unprocessed and Wiener filter processed conditions.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages6520-6524
Number of pages5
ISBN (Electronic)9781479999880
DOIs
Publication statusPublished - 18 May 2016
Externally publishedYes
Event41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Shanghai, China
Duration: 20 Mar 201625 Mar 2016

Publication series

NameInternational Conference on Acoustics Speech and Signal Processing ICASSP
PublisherIEEE
ISSN (Print)1520-6149

Other

Other41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016
CountryChina
CityShanghai
Period20/03/1625/03/16

Keywords

  • Cochlear implants
  • machine learning
  • neural networks
  • noise reduction
  • speech enhancement

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