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Related Experiment Video

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Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody
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Automatic Prosodic Event Detection Using Acoustic, Lexical, and Syntactic Evidence.

Sankaranarayanan Ananthakrishnan1, Shrikanth S Narayanan

  • 1The authors are with the Signal and Image Processing Institute (SIPI), University of Southern California, Los Angeles, CA 90089 USA (e-mail: ananthak@usc.edu ; shri@sipi.usc.edu ).

IEEE Transactions on Audio, Speech, and Language Processing
|January 6, 2009
PubMed
Summary

This study developed an automatic system to detect prosodic events like accent and phrase boundaries in American English speech. The system achieved high accuracy, aiding speech technology applications.

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Area of Science:

  • Computational Linguistics
  • Speech Processing

Background:

  • Prosody annotation standards like ToBI enable detailed speech analysis.
  • Prosodic events offer crucial information beyond segmental and lexical features.
  • Understanding prosody aids spoken language applications and speech synthesis.

Purpose of the Study:

  • To develop an automatic detector and classifier for prosodic events in American English.
  • To leverage acoustic, lexical, and syntactic correlates for prosodic event detection.
  • To focus on syllable-level accent and prosodic phrase boundary detection.

Main Methods:

  • Utilized acoustic, lexical, and syntactic features for detection.
  • Developed an automatic system for accent and phrase boundary classification.
  • Trained and evaluated the system on the Boston University Radio News Corpus.

Main Results:

  • Achieved 86.75% agreement for accent detection.
  • Achieved 91.61% agreement for prosodic phrase boundary detection.
  • Demonstrated effective automatic detection of key prosodic events.

Conclusions:

  • Automatic prosodic event detection is feasible and accurate.
  • The developed system shows promise for enhancing spoken language technologies.
  • Further research can build upon these findings for improved speech applications.