Post-error Correction in Automatic Speech Recognition Using Discourse Information
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 tha...
Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
Stefan cel Mare University of Suceava
2014-05-01
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Series: | Advances in Electrical and Computer Engineering |
Subjects: | |
Online Access: | http://dx.doi.org/10.4316/AECE.2014.02009 |
Summary: | 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. |
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ISSN: | 1582-7445 1844-7600 |