Publication: Speech and prosodic processing for assistive technology
2
Issued Date
2013-07-16
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2-s2.0-85021346390
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Mahidol University
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SCOPUS
Bibliographic Citation
Computational Approaches to Assistive Technologies for People with Disabilities. Vol.253, (2013), 36-48
Suggested Citation
Lalita Narupiyakul, Vlado Keselj, Nick Cercone, Booncharoen Sirinaovakuld Speech and prosodic processing for assistive technology. Computational Approaches to Assistive Technologies for People with Disabilities. Vol.253, (2013), 36-48. doi:10.3233/978-1-61499-258-5-36 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/31637
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Title
Speech and prosodic processing for assistive technology
Abstract
© 2013 The authors and IOS Press. All rights reserved. A speaker's utterance may convey different meanings to a hearer than what the speaker intended. Such ambiguities can be resolved by emphasizing accents at different positions. In human communication, the utterances are emphasized at a focus part to distinguish the important content and reduce ambiguity in the utterance. In our Focus-to-Emphasize Tone (FET) system, we determine how the speaker's utterances are influenced by focus and speaker's intention. The relationships of focus information, speaker's intention and prosodic phenomena are investigated to recognize the intonation patterns and annotate the sentence with prosodic marks. We propose using the Focus to Emphasize Tone (FET) analysis, which includes: (i) generating the constraints for foci, speaker's intention and prosodic features, (ii) defining the intonation patterns, and (iii) labelling a set of prosodic marks for a sentence. We also design the FET structure to support our analysis and to contain focus, speaker's intention and prosodic components. An implementation of the system is described and the evaluation results on the CMU Communicator (CMU-COM) dataset are presented.