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Relationship between speech recognition in noise and sparseness

Li, Guoping, Lutman, Mark E., Wang, Shouyan and Bleeck, Stefan (2012) Relationship between speech recognition in noise and sparseness International Journal of Audiology, 51, (2), pp. 75-82. (doi:10.3109/14992027.2011.625984). (PMID:22107445).

Record type: Article


Established methods for predicting speech recognition in noise require knowledge of clean speech signals, placing limitations on their application. The study evaluates an alternative approach based on characteristics of noisy speech, specifically its sparseness as represented by the statistic kurtosis. Design: Experiments 1 and 2 involved acoustic analysis of vowel-consonant-vowel (VCV) syllables in babble noise, comparing kurtosis, glimpsing areas, and extended speech intelligibility index (ESII) of noisy speech signals with one another and with pre-existing speech recognition scores. Experiment 3 manipulated kurtosis of VCV syllables and investigated effects on speech recognition scores in normal-hearing listeners. Study sample: Pre-existing speech recognition data for Experiments 1 and 2; seven normal-hearing participants for Experiment 3. Results: Experiments 1 and 2 demonstrated that kurtosis calculated in the time-domain from noisy speech is highly correlated (r > 0.98) with established prediction models: glimpsing and ESII. All three measures predicted speech recognition scores well. The final experiment showed a clear monotonic relationship between speech recognition scores and kurtosis. Conclusions: Speech recognition performance in noise is closely related to the sparseness (kurtosis) of the noisy speech signal, at least for the types of speech and noise used here and for listeners with normal hearing

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e-pub ahead of print date: 22 November 2011
Published date: February 2012
Keywords: glimpsing, babble, speech intelligibility index, cocktail party effect
Organisations: Human Sciences Group


Local EPrints ID: 334268
PURE UUID: d77c9cc1-41eb-40a8-ae42-4023c1f23298
ORCID for Stefan Bleeck: ORCID iD

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Date deposited: 06 Mar 2012 14:53
Last modified: 18 Jul 2017 06:12

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Author: Guoping Li
Author: Mark E. Lutman
Author: Shouyan Wang
Author: Stefan Bleeck ORCID iD

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