Open AccessPost-error Correction in Automatic Speech Recognition Using Discourse Information
Author(s) -
Sangwoo Kang,
J.-H. Kim,
Jungyun Seo
Publication year - 2014
Publication title -
advances in electrical and computer engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 23
eISSN - 1844-7600
pISSN - 1582-7445
DOI - 10.4316/aece.2014.02009
Subject(s) - speech recognition , computer science , natural language processing , error detection and correction , artificial intelligence , algorithm
Overcoming speech recognition errors in the field of humancomputer 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