On the Enhancement of Intelligibility

Investigating the influence of different speech modifications on the intelligibility of speech in near-end noise

Bachelor thesis (2019)

Authors

B.D.A. Luppes Electrical Engineering, Mathematics and Computer Science
E.H.J. Riemens Electrical Engineering, Mathematics and Computer Science

Contributors

R.C. Hendriks Signal Processing Systems - EEMCS (supervisor 1)
A. Koutrouvelis Signal Processing Systems - EEMCS (supervisor 1)
Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright: © 2019 Bob Luppes, Ellen Riemens
Intelligibility Speech enhancement Speech modifications
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Published Date

21-06-2019

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

Several algorithms to enhance the intelligibility of speech in near-end noise were analyzed and implemented. The algorithms considered were assessed based on the intrusive instrumental intelligibility metric SIIB_Gauss. An implementation based on the direct optimization for this metric is assessed, as well as an implementation based on human induced speech modifications, including increased sound intensity, flattening of the spectral tilt, increased vowel duration and increased consonant-vowel ratio. Another implemented algorithm is the amplification of the transient component of speech. Results show that for increased vowel duration a decrease in intelligibility was found in SIIB_Gauss value as well as in informal listening tests. The other implementations did show an increase in intelligibility according to SIIB_Gauss at SNRs between -4 dB and 6 dB in both stationary and fluctuating noise, under a power constraint. Finally, the implementations were combined into a system that automatically selects the optimal algorithm to use under the given noise conditions. It is shown that this combined system is able to increase intelligibility of speech in the presence of non-fluctuating noise, fluctuating noise, speech shaped noise, and competing speaker noise.