Title
Improving Speech Recognition Using Semantic and Reference Features in a Multimodal Dialog System
Abstract
Current Speech-based dialog system undergo a practical problem; a speech recognizer is defective due to inevitable errors. Even in multimodal dialog systems, which have multiple input channels, errors in the speech recognition are a major problem because speech contains a large portion of user's intention. In this paper, we propose a re-ranking method to improve the performance of speech recognition in a multimodal dialog system. To re-rank the n-best speech recognition hypotheses, we use the multimodal understanding features that are orthogonal to the speech as well as the speech recognizer features. We demonstrate our method to smart home domain, and the results show that the multimodal understanding features are promising in overcoming many speech errors.
Year
DOI
Venue
2007
10.1109/ROMAN.2007.4415120
RO-MAN
Keywords
Field
DocType
multimodal dialog system,speech recognition,re-ranking method,multimodal understanding feature,interactive systems,smart home
Speech corpus,Speech processing,Speech analytics,Voice activity detection,Audio mining,Computer science,Speech recognition,Dialog system,Artificial intelligence,Natural language processing,Speech technology,Acoustic model
Conference
ISBN
Citations 
PageRank 
978-1-4244-1635-6
1
0.37
References 
Authors
7
3
Name
Order
Citations
PageRank
Kyungduk Kim115412.10
Minwoo Jeong214213.89
Gary Geunbae Lee393293.23