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  Using Conditional Random Fields to Predict Pitch Accent in Conversational Speech

Gregory, M., & Altun, Y. (2004). Using Conditional Random Fields to Predict Pitch Accent in Conversational Speech. In D. Scott, W. Daelemans, & M. Walker (Eds.), 42nd Annual Meeting of the Association for Computational Linguistics (ACL 2004) (pp. 677-684). East Stroudsburg, PA, USA: Association for Computational Linguistics.

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 Creators:
Gregory, M, Author
Altun, Y1, Author              
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1External Organizations, ou_persistent22              

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 Abstract: The detection of prosodic characteristics is an important aspect of both speech synthesis and speech recognition. Correct placement of pitch accents aids in more natural sounding speech, while automatic detection of accents can contribute to better wordlevel recognition and better textual understanding. In this paper we investigate probabilistic, contextual, and phonological factors that influence pitch accent placement in natural, conversational speech in a sequence labeling setting. We introduce Conditional Random Fields (CRFs) to pitch accent prediction task in order to incorporate these factors efficiently in a sequence model. We demonstrate the usefulness and the incremental effect of these factors in a sequence model by performing experiments on hand labeled data from the Switchboard Corpus. Our model outperforms the baseline and previous models of pitch accent prediction on the Switchboard Corpus.

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 Dates: 2004-07
 Publication Status: Published in print
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: GregoryA2004
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Title: 42nd Annual Meeting of the Association for Computational Linguistics (ACL 2004)
Place of Event: Barcelona, Spain
Start-/End Date: 2004-07-21 - 2004-07-26

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Title: 42nd Annual Meeting of the Association for Computational Linguistics (ACL 2004)
Source Genre: Proceedings
 Creator(s):
Scott, D, Editor
Daelemans, W, Editor
Walker, M, Editor
Affiliations:
-
Publ. Info: East Stroudsburg, PA, USA : Association for Computational Linguistics
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 677 - 684 Identifier: ISBN: 1-932432-34-5