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Implications of prosody modeling for prosody recognition

Abstract:
This paper introduces Stem-ML, which is a model of the prosody generation process with an associated description language, and suggests how it may help prosody recognition. We applied Stem-ML modeling to three topics: the modeling of prosodic strengths, intonation types, and noun phrase patterns. Stem-ML parameters derived from F0 contours may have a more consistent relationship with prosodic events than raw F0 values. This may improve identification of accent classes, accent strengths, and intonation types.
Publication status:
Published
Peer review status:
Not peer reviewed
Version:
Author's Original

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Institution:
"Bell Laboratories, Lucent Technologies"
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Author
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Institution:
University of Oxford
Department:
Humanities Division - Linguistics & Phonetics - Phonetics
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Institution:
"Bell Laboratories, Lucent Technologies"
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Institution:
Yale University
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Institution:
Cornell University
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Author
Publisher:
International Speech Communication Association (ISCA) Publisher's website
URN:
uuid:8f2e2f56-b4f7-4345-b5d0-137da19cf1da
Local pid:
ora:9952

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