Improving the Readability of Class Lecture Automatic Speech Recognition Results Using Multiple Hypotheses

Abstract

This paper presents a method for improving the readability of class lecture Automatic Speech Recognition (ASR) results, which hitherto have been difficult for humans to understand, even in the absence of recognition errors. This is because the speech in a class lecture is relatively casual and contains many ill-formed utterances with filled pauses, restarts… (More)

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Cite this paper

@inproceedings{Fujii2009ImprovingTR, title={Improving the Readability of Class Lecture Automatic Speech Recognition Results Using Multiple Hypotheses}, author={Yasuhisa Fujii and Kazumasa Yamamoto and Seiichi Nakagawa}, year={2009} }