Using Conditional Random Fields to Predict Pitch Accent in Conversational Speech

Gregory, M; Altun, Y

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Using Conditional Random Fields to Predict Pitch Accent in Conversational Speech

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https://ttic.uchicago.edu/~altun/pubs/GregoryAltun.pdf
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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.

Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-D8AD-F

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.