Improved language model adaptation using existing and derived external resources
Journal
2003 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2003
Pages
531-536
Date Issued
2003
Author(s)
Chang, P.-C.
Abstract
Adaptation of language models to obtain better parameters for the topics addressed by the spoken documents to be recognized has been a key issue for speech recognition. In this paper, we propose to collect existing as well as derived external resources for improved language model adaptation. The derived external resources are those retrieved based on the baseline transcriptions for the input spoken documents from the Internet using some search engine. The design of queries for such purposes are also analyzed in this paper, in which the special structure of Chinese language is considered. The obtained existing and derived external resources are then used in the model adaptation under a Clustering-Classification framework. Very encouraging results were obtained in the preliminary experiments with two test sets: broadcast news and interview recording. © 2003 IEEE.
Event(s)
IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2003
SDGs
Other Subjects
Computational linguistics; Search engines; Broadcast news; Chinese language; Clustering classifications; External resources; Language model adaptation; Model Adaptation; Special structure; Spoken document; Speech recognition
Type
conference paper