Paper Info
Title
Using Dialogue-Based Dynamic Language Models For Improving Speech Recognition
Abstract
We present a new approach to dynamically create and manage different language models to be used on a spoken dialogue system. We apply an interpolation based approach, using several measures obtained by the Dialogue Manager to decide what LM the system will interpolate and also to estimate the interpolation weights. We propose to use not only semantic information (the concepts extracted from each recognized utterance), but also information obtained by the dialogue manager module (DM), that is, the objectives or goals the user wants to fulfill, and the proper classification of those concepts according to the inferred goals. The experiments we have carried out show improvements over word error rate when using the parsed concepts and the inferred goals from a speech utterance for rescoring the same utterance.
Year
Venue
Keywords
2009
INTERSPEECH 2009: 10TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2009, VOLS 1-5
spoken dialogue systems, dynamic language modeling, automatic speech recognition
Field
DocType
Citations 
Computer science,Word error rate,Interpolation,Utterance,Speech recognition,Semantic information,Natural language processing,Artificial intelligence,Parsing,Language model
Conference
3
PageRank 
References 
Authors
0.43
10
3
Name
Order
Citations
PageRank
Juan Manuel Lucas-Cuesta1354.37
Fernando Fernández-Martínez2489.27
Javier Ferreiros330.43