Abstract
Automatic speech recognition (ASR) technology has achieved a level of maturity, where it is already practical to be used by novice users. However, most non-native speakers are still not comfortable with services including ASR systems, because of the accuracy on non-native speakers. This paper describes our approach in constructing a non-native corpus particularly in French for testing and adapting non-native speaker for automatic speech recognition. Finally, we also propose in this paper a method for detecting pronunciation variants and possible pronunciation mistakes by non-native speakers.- Anthology ID:
- L06-1012
- Volume:
- Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)
- Month:
- May
- Year:
- 2006
- Address:
- Genoa, Italy
- Editors:
- Nicoletta Calzolari, Khalid Choukri, Aldo Gangemi, Bente Maegaard, Joseph Mariani, Jan Odijk, Daniel Tapias
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association (ELRA)
- Note:
- Pages:
- Language:
- URL:
- http://www.lrec-conf.org/proceedings/lrec2006/pdf/33_pdf.pdf
- DOI:
- Cite (ACL):
- Tien-Ping Tan and Laurent Besacier. 2006. A French Non-Native Corpus for Automatic Speech Recognition. In Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06), Genoa, Italy. European Language Resources Association (ELRA).
- Cite (Informal):
- A French Non-Native Corpus for Automatic Speech Recognition (Tan & Besacier, LREC 2006)
- PDF:
- http://www.lrec-conf.org/proceedings/lrec2006/pdf/33_pdf.pdf