Speech recognition of a named entity
Tomoya Tomita, Yoshiyuki Okimoto, Hirotsugu Yamamoto, Yoshinori Sagisaka · 2006
A hierarchical language model is newly applied to identify a named entity consisting of multiple word sequences for continuous speech recognition. By redesigning an out-of-vocabulary model of a single word using phonotactic constraints for a named entity, a hierarchical model is composed harmoniously with conventional word and word-class N-grams. Continuous speech recognition experiments aimed at movie-title identification showed the effectiveness of this modeling in the task of inquiries on these titles. These results ensure that the proposed hierarchical language modeling architecture is applicable to multiple word successions for speech recognition to cope with unregistered expressions and enables the mixed use of different statistics harmoniously.