Objective measures for predicting the intelligibility of spectrally smoothed speech with artificial excitation

Websdale, Danny, Le Cornu, Thomas and Milner, Ben (2015) Objective measures for predicting the intelligibility of spectrally smoothed speech with artificial excitation. In: Interspeech 2015, 2015-09-06 - 2015-09-10.

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Abstract

A study is presented on how well objective measures of speech quality and intelligibility can predict the subjective in- telligibility of speech that has undergone spectral envelope smoothing and simplification of its excitation. Speech modi- fications are made by resynthesising speech that has been spec- trally smoothed. Objective measures are applied to the mod- ified speech and include measures of speech quality, signal- to-noise ratio and intelligibility, as well as proposing the nor- malised frequency-weighted spectral distortion (NFD) measure. The measures are compared to subjective intelligibility scores where it is found that several have high correlation (|r| ≥ 0.7), with NFD achieving the highest correlation (r = −0.81)

Item Type:	Conference or Workshop Item (Paper)
Faculty \ School:	Faculty of Science > School of Computing Sciences Faculty of Science
UEA Research Groups:	Faculty of Science > Research Groups > Interactive Graphics and Audio Faculty of Science > Research Groups > Smart Emerging Technologies
Depositing User:	Pure Connector
Date Deposited:	23 Dec 2015 13:00
Last Modified:	08 Mar 2024 00:58
URI:	https://ueaeprints.uea.ac.uk/id/eprint/55879
DOI:

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