Acoustic Word Disambiguation with Phonogical Features in Danish ASR

Andreas Søeborg Kirkedal


Abstract
Phonological features can indicate word class and we can use word class information to disambiguate both homophones and homographs in automatic speech recognition (ASR). We show Danish stød can be predicted from speech and used to improve ASR. We discover which acoustic features contain the signal of stød, how to use these features to predict stød and how we can make use of stød and stødpredictive acoustic features to improve overall ASR accuracy and decoding speed. In the process, we discover acoustic features that are novel to the phonetic characterisation of stød.
Anthology ID:
W18-5803
Volume:
Proceedings of the Fifteenth Workshop on Computational Research in Phonetics, Phonology, and Morphology
Month:
October
Year:
2018
Address:
Brussels, Belgium
Venues:
EMNLP | WS
SIG:
SIGMORPHON
Publisher:
Association for Computational Linguistics
Note:
Pages:
21–31
Language:
URL:
https://www.aclweb.org/anthology/W18-5803
DOI:
10.18653/v1/W18-5803
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/W18-5803.pdf