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Supervised sparse coding strategy in cochlear implants

Supervised sparse coding strategy in cochlear implants
Supervised sparse coding strategy in cochlear implants

In this paper we explore how to improve a sparse coding (SC) strategy that was successfully used to improve subjective speech perception in noisy environment in cochlear implants. On the basis of the existing unsupervised algorithm, we developed an enhanced supervised SC strategy, using the SC shrinkage (SCS) principle. The new algorithm is implemented at the stage of the spectral envelopes after the signal separation in a 22-channel filter bank. SCS can extract and transmit the most important information from noisy speech. The new algorithm is compared with the unsupervised algorithm using objective evaluation for speech in babble and white noise (signal-to-noise ratios, SNR = 10dB, 5dB, 0dB) using objective measures in a cochlea implant simulation. Results show that the supervised SC strategy performs better in white noise, but not significantly better with babble noise.

Cochlear implants, Sparse coding, Supervised learning
1793-1796
Sang, Jinqiu
0265ab21-0646-4451-a874-022c92ca2dc2
Li, Guoping
b791b5c0-52cb-4311-b0de-3d6b2f289835
Hu, Hongmei
619a5602-4865-4100-9be9-f31572a0953d
Lutman, Mark E.
add34340-3241-4346-a668-8f51fdea6692
Bleeck, Stefan
c888ccba-e64c-47bf-b8fa-a687e87ec16c
Sang, Jinqiu
0265ab21-0646-4451-a874-022c92ca2dc2
Li, Guoping
b791b5c0-52cb-4311-b0de-3d6b2f289835
Hu, Hongmei
619a5602-4865-4100-9be9-f31572a0953d
Lutman, Mark E.
add34340-3241-4346-a668-8f51fdea6692
Bleeck, Stefan
c888ccba-e64c-47bf-b8fa-a687e87ec16c

Sang, Jinqiu, Li, Guoping, Hu, Hongmei, Lutman, Mark E. and Bleeck, Stefan (2011) Supervised sparse coding strategy in cochlear implants. 12th Annual Conference of the International Speech Communication Association, INTERSPEECH 2011, Florence, Italy. 27 - 31 Aug 2011. pp. 1793-1796 .

Record type: Conference or Workshop Item (Paper)

Abstract

In this paper we explore how to improve a sparse coding (SC) strategy that was successfully used to improve subjective speech perception in noisy environment in cochlear implants. On the basis of the existing unsupervised algorithm, we developed an enhanced supervised SC strategy, using the SC shrinkage (SCS) principle. The new algorithm is implemented at the stage of the spectral envelopes after the signal separation in a 22-channel filter bank. SCS can extract and transmit the most important information from noisy speech. The new algorithm is compared with the unsupervised algorithm using objective evaluation for speech in babble and white noise (signal-to-noise ratios, SNR = 10dB, 5dB, 0dB) using objective measures in a cochlea implant simulation. Results show that the supervised SC strategy performs better in white noise, but not significantly better with babble noise.

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More information

Published date: 1 December 2011
Venue - Dates: 12th Annual Conference of the International Speech Communication Association, INTERSPEECH 2011, Florence, Italy, 2011-08-27 - 2011-08-31
Keywords: Cochlear implants, Sparse coding, Supervised learning

Identifiers

Local EPrints ID: 436060
URI: http://eprints.soton.ac.uk/id/eprint/436060
PURE UUID: ad9e1a16-ae1f-43d8-b899-95386e2b76bb
ORCID for Stefan Bleeck: ORCID iD orcid.org/0000-0003-4378-3394

Catalogue record

Date deposited: 27 Nov 2019 17:30
Last modified: 17 Dec 2019 01:45

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Contributors

Author: Jinqiu Sang
Author: Guoping Li
Author: Hongmei Hu
Author: Mark E. Lutman
Author: Stefan Bleeck ORCID iD

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