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Low-Resource Speech Recognition and Keyword-Spotting Read chapter Read first chapter

2017 | OriginalPaper | Chapter

Hesitations in Spontaneous Speech: Acoustic Analysis and Detection

Authors : Vasilisa Verkhodanova, Vladimir Shapranov, Irina Kipyatkova

Published in: Speech and Computer

Publisher: Springer International Publishing

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Abstract

Spontaneous speech is different from any other type of speech in many ways, with speech disfluencies being the prominent feature. These phenomena both play an important role in communication, and also cause problems for automatic speech processing. In this study we present the results of acoustic analysis of the most frequent disfluencies - voiced hesitations (filled pauses and lengthenings) across different speaking styles in spontaneous Russian speech, as well as results of experiments on their detection using SVM classifier on a joint Russian and English spontaneous speech corpus. Results of acoustic analysis showed significant differences in fundamental frequency and energy distribution ratios of hesitations and their contexts across speaking styles in Russian: comparing to the dialogues, in monologues speakers exhibit more prosodic cues for the adjacent context and hesitations. Experiments on detection of voiced hesitations on a mixed language and style corpus with SVM resulted in achieving F1–score = 0.48 (With F1–score = 0.55 for only Russian data).

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previous chapter Fusion of a Novel Volterra-Wiener Filter Based Nonlinear Residual Phase and MFCC for Speaker Verification
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Metadata
Title
Hesitations in Spontaneous Speech: Acoustic Analysis and Detection
Authors
Vasilisa Verkhodanova
Vladimir Shapranov
Irina Kipyatkova
Copyright Year
2017
Book
Speech and Computer

Print ISBN: 978-3-319-66428-6

Electronic ISBN: 978-3-319-66429-3

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-66429-3_39

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