Speech and prosodic processing for assistive technology
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 a...
Saved in:
Main Authors: | , , , |
---|---|
Other Authors: | |
Format: | Article |
Published: |
2018
|
Subjects: | |
Online Access: | https://repository.li.mahidol.ac.th/handle/123456789/31604 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Mahidol University |
id |
th-mahidol.31604 |
---|---|
record_format |
dspace |
spelling |
th-mahidol.316042018-10-19T11:50:48Z Speech and prosodic processing for assistive technology Lalita Narupiyakul Vlado Keselj Nick Cercone Booncharoen Sirinaovakul Mahidol University Dalhousie University York University King Mongkuts University of Technology Thonburi Computer Science 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. © 2013 The authors and IOS Press. All rights reserved. 2018-10-19T04:50:48Z 2018-10-19T04:50:48Z 2013-12-01 Article Frontiers in Artificial Intelligence and Applications. Vol.253, (2013), 36-48 10.3233/978-1-61499-258-5-36 09226389 2-s2.0-84894597328 https://repository.li.mahidol.ac.th/handle/123456789/31604 Mahidol University SCOPUS https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84894597328&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 Sirinaovakul Speech and prosodic processing for assistive technology |
description |
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. © 2013 The authors and IOS Press. All rights reserved. |
author2 |
Mahidol University |
author_facet |
Mahidol University Lalita Narupiyakul Vlado Keselj Nick Cercone Booncharoen Sirinaovakul |
format |
Article |
author |
Lalita Narupiyakul Vlado Keselj Nick Cercone Booncharoen Sirinaovakul |
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/123456789/31604 |
_version_ |
1763494595412361216 |