ISCA Archive Interspeech 2009
ISCA Archive Interspeech 2009

Constraint selection for topic-based MDI adaptation of language models

Gwénolé Lecorvé, Guillaume Gravier, Pascale Sébillot

This paper presents an unsupervised topic-based language model adaptation method which specializes the standard minimum information discrimination approach by identifying and combining topic-specific features. By acquiring a topic terminology from a thematically coherent corpus, language model adaptation is restrained to the sole probability re-estimation of n-grams ending with some topic-specific words, keeping other probabilities untouched. Experiments are carried out on a large set of spoken documents about various topics. Results show significant perplexity and recognition improvements which outperform results of classical adaptation techniques.


doi: 10.21437/Interspeech.2009-117

Cite as: Lecorvé, G., Gravier, G., Sébillot, P. (2009) Constraint selection for topic-based MDI adaptation of language models. Proc. Interspeech 2009, 368-371, doi: 10.21437/Interspeech.2009-117

@inproceedings{lecorve09_interspeech,
  author={Gwénolé Lecorvé and Guillaume Gravier and Pascale Sébillot},
  title={{Constraint selection for topic-based MDI adaptation of language models}},
  year=2009,
  booktitle={Proc. Interspeech 2009},
  pages={368--371},
  doi={10.21437/Interspeech.2009-117}
}