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Phonological feature-based speech recognition system for pronunciation training in non-native language learning

Abstract:

The authors address the question whether phonological features can be used effectively in an automatic speech recognition (ASR) system for pronunciation training in non-native language (L2) learning. Computer-aided pronunciation training consists of two essential tasks—detecting mispronunciations and providing corrective feedback, usually either on the basis of full words or phonemes. Phonemes, however, can be further disassembled into phonological features, which in turn define groups of pho...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1121/1.5017834

Authors


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Institution:
University of Oxford
Division:
HUMS
Department:
Linguistics Philology and Phonetics Faculty
Role:
Author
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Institution:
University of Oxford
Division:
Humanities Division
Department:
Ling Philology & Phonetics Fac
Role:
Author
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Name:
European Research Council
Grant:
695481
Publisher:
Acoustical Society of America
Journal:
Journal of the Acoustical Society of America More from this journal
Volume:
143
Issue:
1
Article number:
98
Publication date:
2018-01-08
Acceptance date:
2017-11-28
DOI:
EISSN:
1520-8524
ISSN:
0001-4966
Keywords:
Pubs id:
pubs:820972
UUID:
uuid:d0dade3c-c789-4f5b-81d8-9ce9348ce307
Local pid:
pubs:820972
Source identifiers:
820972
Deposit date:
2018-01-22

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