Can Objective Measures Predict the Intelligibility of Modified HMM-based Synthetic Speech in Noise?

Cassia Valentini-Botinhao; Junichi Yamagishi; Simon King

Can Objective Measures Predict the Intelligibility of Modified HMM-based Synthetic Speech in Noise?

Cassia Valentini-Botinhao, Junichi Yamagishi, Simon King

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Synthetic speech can be modified to improve intelligibility in noise. In order to perform modifications automatically, it would be useful to have an objective measure that could predict the intelligibility of modified synthetic speech for human listeners. We analysed the impact on intelligibility - and on how well objective measures predict it -“ when we separately modify speaking rate, fundamental frequency, line spectral pairs and spectral peaks. Shifting LSPs can increase intelligibility for human listeners; other modifications had weaker effects. Among the objective measures we evaluated, the Dau model and the Glimpse proportion were the best predictors of human performance.

Original language	English
Title of host publication	Interspeech 2011
Subtitle of host publication	12th Annual Conference of the International Speech Communication Association
Publisher	International Speech Communication Association
Pages	1837-1840
Number of pages	4
ISBN (Print)	1990-9772
Publication status	Published - 1 Aug 2011

Access to Document

Can Objective Measures Predict the Intelligibility of Modified HMM-based
© Valentini-Botinhao, C., Yamagishi, J., & King, S. (2011). Can Objective Measures Predict the Intelligibility of Modified HMM-based Synthetic Speech in Noise?. In Interspeech 2011: 12th Annual Conference of the International Speech Communication Association. (pp. 1837-1840). International Speech Communication Association.
Accepted author manuscript, 101 KB

Cite this

@inproceedings{6e58d7b621d843f3967a17f0f9653fbc,

title = "Can Objective Measures Predict the Intelligibility of Modified HMM-based Synthetic Speech in Noise?",

abstract = "Synthetic speech can be modified to improve intelligibility in noise. In order to perform modifications automatically, it would be useful to have an objective measure that could predict the intelligibility of modified synthetic speech for human listeners. We analysed the impact on intelligibility - and on how well objective measures predict it -“ when we separately modify speaking rate, fundamental frequency, line spectral pairs and spectral peaks. Shifting LSPs can increase intelligibility for human listeners; other modifications had weaker effects. Among the objective measures we evaluated, the Dau model and the Glimpse proportion were the best predictors of human performance.",

author = "Cassia Valentini-Botinhao and Junichi Yamagishi and Simon King",

year = "2011",

month = aug,

day = "1",

language = "English",

isbn = "1990-9772",

pages = "1837--1840",

booktitle = "Interspeech 2011",

publisher = "International Speech Communication Association",

}

Can Objective Measures Predict the Intelligibility of Modified HMM-based Synthetic Speech in Noise? / Valentini-Botinhao, Cassia; Yamagishi, Junichi; King, Simon.

Interspeech 2011: 12th Annual Conference of the International Speech Communication Association. International Speech Communication Association, 2011. p. 1837-1840.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution