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The role of syllable intensity in between- speaker rhythmic variability


He, Lei; Dellwo, Volker (2016). The role of syllable intensity in between- speaker rhythmic variability. International Journal of Speech, Language and the Law, 23(2):243-273.

Abstract

Speech rhythm in terms of durational variability of different levels of phonetic intervals can vary between speakers. The present article examines the role of syl- labic intensity characteristics in rhythmic variability. Mean and peak intensity variability across syllables (stdevM, varcoM, stdevP, varcoP, rPVIm, nPVIm, rPVIp, nPVIp; henceforth: intensity measures) were investigated as a function of speaker in a database where within-speaker variability was strong (BonnTempo) and another database designed to examine between-speaker rhythmic variability (TEVOID). It was found that the intensity measures varied significantly between speakers in both databases. Semiautomatic speaker recognition based on duration measures (%V, ∆V(ln), ∆C(ln), ∆Peak(ln), ∆Syll(ln) and nPVISyll) and intensity measures using multinomial logistic regression and feedforward neural networks was carried out for the two databases. Results showed that intensity measures contained stronger speaker specific information compared to measures based on durational variability of phonetic intervals. In addition, effects of the recognition algorithms (speaker rec- ognition using multinomial logistic regression was significantly better than neural networks for BonnTempo) and data normalisation procedures (z-score normalised data was significantly better than non-normalised data in TEVOID) were discov- ered. This means that syllable intensity characteristics play an important role in between-speaker rhythmic differences and possibly in speech rhythm variability in general.

Abstract

Speech rhythm in terms of durational variability of different levels of phonetic intervals can vary between speakers. The present article examines the role of syl- labic intensity characteristics in rhythmic variability. Mean and peak intensity variability across syllables (stdevM, varcoM, stdevP, varcoP, rPVIm, nPVIm, rPVIp, nPVIp; henceforth: intensity measures) were investigated as a function of speaker in a database where within-speaker variability was strong (BonnTempo) and another database designed to examine between-speaker rhythmic variability (TEVOID). It was found that the intensity measures varied significantly between speakers in both databases. Semiautomatic speaker recognition based on duration measures (%V, ∆V(ln), ∆C(ln), ∆Peak(ln), ∆Syll(ln) and nPVISyll) and intensity measures using multinomial logistic regression and feedforward neural networks was carried out for the two databases. Results showed that intensity measures contained stronger speaker specific information compared to measures based on durational variability of phonetic intervals. In addition, effects of the recognition algorithms (speaker rec- ognition using multinomial logistic regression was significantly better than neural networks for BonnTempo) and data normalisation procedures (z-score normalised data was significantly better than non-normalised data in TEVOID) were discov- ered. This means that syllable intensity characteristics play an important role in between-speaker rhythmic differences and possibly in speech rhythm variability in general.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:06 Faculty of Arts > Department of Comparative Linguistics
06 Faculty of Arts > Institute of Computational Linguistics
Dewey Decimal Classification:000 Computer science, knowledge & systems
490 Other languages
890 Other literatures
410 Linguistics
Language:English
Date:December 2016
Deposited On:10 Nov 2016 10:33
Last Modified:29 May 2017 07:33
Publisher:Equinox Publishing Ltd.
ISSN:1748-8885
Publisher DOI:https://doi.org/10.1558/ijsll.v23i2.30345
Related URLs:https://journals.equinoxpub.com/index.php/IJSLL/index (Publisher)

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