ISCA Archive Interspeech 2008
ISCA Archive Interspeech 2008

Unsupervised language model adaptation based on topic and role information in multiparty meetings

Songfang Huang, Steve Renals

We continue our previous work on the modeling of topic and role information from multiparty meetings using a hierarchical Dirichlet process (HDP), in the context of language model adaptation. In this paper we focus on three problems: 1) an empirical analysis of the HDP as a nonparametric topic model; 2) the mismatch problem of vocabularies of the baseline n-gram model and the HDP; and 3) an automatic speech recognition experiment to further verify the effectiveness of our adaptation framework. Experiments on a large meeting corpus of more than 70 hours speech data show consistent and significant improvements in terms of word error rate for language model adaptation based on the topic and role information.


doi: 10.21437/Interspeech.2008-253

Cite as: Huang, S., Renals, S. (2008) Unsupervised language model adaptation based on topic and role information in multiparty meetings. Proc. Interspeech 2008, 833-836, doi: 10.21437/Interspeech.2008-253

@inproceedings{huang08b_interspeech,
  author={Songfang Huang and Steve Renals},
  title={{Unsupervised language model adaptation based on topic and role information in multiparty meetings}},
  year=2008,
  booktitle={Proc. Interspeech 2008},
  pages={833--836},
  doi={10.21437/Interspeech.2008-253}
}