Detecting pitch accents at the word, syllable and vowel level

Authors:
Andrew Rosenberg;Julia Hirschberg
Affiliations:
Columbia University;Columbia University
Venue:
NAACL-Short '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers
Year:
2009

Citing 2
Cited 3

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Abstract

The automatic identification of prosodic events such as pitch accent in English has long been a topic of interest to speech researchers, with applications to a variety of spoken language processing tasks. However, much remains to be understood about the best methods for obtaining high accuracy detection. We describe experiments examining the optimal domain for accent analysis. Specifically, we compare pitch accent identification at the syllable, vowel or word level as domains for analysis of acoustic indicators of accent. Our results indicate that a word-based approach is superior to syllable- or vowel-based detection, achieving an accuracy of 84.2%.