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- W2783805655 abstract "This paper presents the results of experiments in recognition of whispered speech, as a specific mode of verbal communication, using SVM (Support Vector Machines) classifier. For training and testing purposes, part of the speech database Whi-Spe with male speakers has been exploited. In matched scenarios average word recognition rate was 99.3% (for normally phonated speech) and 97.8% (for whisper). In mismatched scenarios, recognition of whisper with training on normal speech utterances was 75.4%, whereas recognition of whisper-trained normal speech was with recognition rate of 81.3%." @default.
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- W2783805655 date "2017-11-01" @default.
- W2783805655 modified "2023-10-18" @default.
- W2783805655 title "Recognition of bimodal produced speech based on Support Vector Machines" @default.
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- W2783805655 doi "https://doi.org/10.1109/telfor.2017.8249360" @default.
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