Prosody toolkit: Integrating HTK, Praat and WEKA

S. Thomas Christie, Serguei V Pakhomov

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations

Abstract

A major hurdle in computational speech analysis is the effective integration of available tools originally developed for purposes unrelated to each other. We present a Python-based tool to enable an efficient and organized processing workflow incorporating automatic speech recognition using HTK, phonemelevel prosodic feature extraction in Praat and machine learning in WEKA. Our system is extensible, customizable and organizes prosodic data by phoneme and time stamp in a tabular fashion in preparation for analysis using other utilities. Plotting of prosodic information is supported to enable visualization of prosodic features.

Original languageEnglish (US)
Pages (from-to)3321-3322
Number of pages2
JournalProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
StatePublished - 2011
Event12th Annual Conference of the International Speech Communication Association, INTERSPEECH 2011 - Florence, Italy
Duration: Aug 27 2011Aug 31 2011

Keywords

  • HTK
  • Praat
  • Prosody
  • Python
  • WEKA

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