Exploring Practical Metrics to Support Automatic Speech Recognition Evaluations
E.A. Draffan,
Mike Wald,
Chaohai Ding
et al.
Abstract:Recent studies into the evaluation of automatic speech recognition for its quality of output in the form of text have shown that using word error rate to see how many mistakes exist in English does not necessarily help the developer of automatic transcriptions or captions. Confidence levels as to the type of errors being made remain low because mistranslations from speech to text are not always captured with a note that details the reason for the error. There have been situations in higher education where stud… Show more
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