학술논문
Post-error Correction in Automatic Speech Recognition Using Discourse Information
Document Type
article
Author
Source
Advances in Electrical and Computer Engineering, Vol 14, Iss 2, Pp 53-56 (2014)
Subject
Language
English
ISSN
1582-7445
1844-7600
1844-7600
Abstract
Overcoming speech recognition errors in the field of human�computer interaction is important in ensuring a consistent user experience. This paper proposes a semantic-oriented post-processing approach for the correction of errors in speech recognition. The novelty of the model proposed here is that it re-ranks the n-best hypothesis of speech recognition based on the user's intention, which is analyzed from previous discourse information, while conventional automatic speech recognition systems focus only on acoustic and language model scores for the current sentence. The proposed model successfully reduces the word error rate and semantic error rate by 3.65% and 8.61%, respectively.