ISCA Archive ICSLP 2000
ISCA Archive ICSLP 2000

Automatic detection of mispronounced phonemes for language learning tools

Olivier Deroo, Christophe Ris, Sofie Gielen, Johan Vanparys

Automatic Speech Recognition (ASR) can be very useful in language learning tools in order to correct mistakes in the pronunciation of foreign words by non-native speakers. Most of the systems integrating ASR proposed on the market are just rejecting or accepting whole words or whole sentences. In this paper, we propose a method to identify the pronunciation errors at the phoneme level. Indeed, mistakes are often predictable and concern a particular subset of phonemes not present in the mother language of the speaker. We describe two different approaches based on the Hybrid HMM/ANN technology. The methodology for the training of the recognizer is discussed, and we describe a new approach where a mixed database is used to train a speech recognition system able to detect pronunciation errors at the phoneme level. Preliminary but promising results have been obtained on the DEMOSTHENES database.


Cite as: Deroo, O., Ris, C., Gielen, S., Vanparys, J. (2000) Automatic detection of mispronounced phonemes for language learning tools. Proc. 6th International Conference on Spoken Language Processing (ICSLP 2000), vol. 1, 681-684

@inproceedings{deroo00_icslp,
  author={Olivier Deroo and Christophe Ris and Sofie Gielen and Johan Vanparys},
  title={{Automatic detection of mispronounced phonemes for language learning tools}},
  year=2000,
  booktitle={Proc. 6th International Conference on Spoken Language Processing (ICSLP 2000)},
  pages={vol. 1, 681-684}
}