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
- Editors:
- Sandra Kuebler, Garrett Nicolai
- Venue:
- EMNLP
- SIG:
- SIGMORPHON
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 21–31
- Language:
- URL:
- https://aclanthology.org/W18-5803
- DOI:
- 10.18653/v1/W18-5803
- Cite (ACL):
- Andreas Søeborg Kirkedal. 2018. Acoustic Word Disambiguation with Phonogical Features in Danish ASR. In Proceedings of the Fifteenth Workshop on Computational Research in Phonetics, Phonology, and Morphology, pages 21–31, Brussels, Belgium. Association for Computational Linguistics.
- Cite (Informal):
- Acoustic Word Disambiguation with Phonogical Features in Danish ASR (Kirkedal, EMNLP 2018)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/W18-5803.pdf