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Hesitations in Spontaneous Speech: Acoustic Analysis and Detection

  • Vasilisa VerkhodanovaEmail author
  • Vladimir Shapranov
  • Irina Kipyatkova
Conference paper
  • 1.6k Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10458)

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).

Keywords

Speech disfluencies Hesitations Filled pauses Lengthenings Speech processing Support vector machines 

Notes

Acknowledgments

This research is supported by the grant of Russian Foundation for Basic Research (project No. 15-06-04465) and by the Council for Grants of the President of the Russian Federation (projects No. MK-1000.2017.8).

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Vasilisa Verkhodanova
    • 1
    Email author
  • Vladimir Shapranov
    • 1
  • Irina Kipyatkova
    • 1
  1. 1.SPIIRASSt. PetersburgRussia

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