Speech and prosodic processing for assistive technology

© 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...

Full description

Saved in:
Bibliographic Details
Main Authors: Lalita Narupiyakul, Vlado Keselj, Nick Cercone, Booncharoen Sirinaovakuld
Other Authors: Mahidol University
Format: Chapter
Published: 2018
Subjects:
Online Access:https://repository.li.mahidol.ac.th/handle/123456789/31637
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Mahidol University
id th-mahidol.31637
record_format dspace
spelling th-mahidol.316372018-10-19T11:51:49Z Speech and prosodic processing for assistive technology Lalita Narupiyakul Vlado Keselj Nick Cercone Booncharoen Sirinaovakuld Mahidol University Dalhousie University York University King Mongkuts University of Technology Thonburi Computer Science © 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. 2018-10-19T04:51:49Z 2018-10-19T04:51:49Z 2013-07-16 Chapter Computational Approaches to Assistive Technologies for People with Disabilities. Vol.253, (2013), 36-48 10.3233/978-1-61499-258-5-36 2-s2.0-85021346390 https://repository.li.mahidol.ac.th/handle/123456789/31637 Mahidol University SCOPUS https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85021346390&origin=inward
institution Mahidol University
building Mahidol University Library
continent Asia
country Thailand
Thailand
content_provider Mahidol University Library
collection Mahidol University Institutional Repository
topic Computer Science
spellingShingle Computer Science
Lalita Narupiyakul
Vlado Keselj
Nick Cercone
Booncharoen Sirinaovakuld
Speech and prosodic processing for assistive technology
description © 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.
author2 Mahidol University
author_facet Mahidol University
Lalita Narupiyakul
Vlado Keselj
Nick Cercone
Booncharoen Sirinaovakuld
format Chapter
author Lalita Narupiyakul
Vlado Keselj
Nick Cercone
Booncharoen Sirinaovakuld
author_sort Lalita Narupiyakul
title Speech and prosodic processing for assistive technology
title_short Speech and prosodic processing for assistive technology
title_full Speech and prosodic processing for assistive technology
title_fullStr Speech and prosodic processing for assistive technology
title_full_unstemmed Speech and prosodic processing for assistive technology
title_sort speech and prosodic processing for assistive technology
publishDate 2018
url https://repository.li.mahidol.ac.th/handle/123456789/31637
_version_ 1763489651470893056