ProTK: An improved prosody toolkit

Jacob Okamoto, Serguei V Pakhomov, Elizabeth Shriberg, Andreas Stolcke

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We present an improvement to our previous work to create a toolkit for integrating automated speech recognition, prosodic feature analysis, and machine learning to create models for identifying and classifying speech characteristics such as filled pauses. The toolkit provides a modular and extensible platform for intaking, analyzing, and formatting data for use in a wide variety of other tools.

Original languageEnglish (US)
Title of host publication13th Annual Conference of the International Speech Communication Association 2012, INTERSPEECH 2012
Pages1890-1891
Number of pages2
StatePublished - Dec 1 2012
Event13th Annual Conference of the International Speech Communication Association 2012, INTERSPEECH 2012 - Portland, OR, United States
Duration: Sep 9 2012Sep 13 2012

Publication series

Name13th Annual Conference of the International Speech Communication Association 2012, INTERSPEECH 2012
Volume3

Other

Other13th Annual Conference of the International Speech Communication Association 2012, INTERSPEECH 2012
CountryUnited States
CityPortland, OR
Period9/9/129/13/12

Keywords

  • Machine learning
  • Prosody
  • Speech recognition
  • Toolkit

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