Acoustic Word Disambiguation with Phonogical Features in Danish ASR
Phonological features can indicate word class and we can use word class information to disambiguate both homophones and homographs in automatic speech recognition (ASR). We show Danish st{\o}d can be predicted from speech and used to improve ASR. We discover which acoustic features contain the signal of st{\o}d, how to use these features to predict st{\o}d and how we can make use of st{\o}d and st{\o}dpredictive acoustic features to improve overall ASR accuracy and decoding speed. In the process, we discover acoustic features that are novel to the phonetic characterisation of st{\o}d.
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Automatic Speech RecognitionAutomatic Speech Recognition (ASR)speech-recognitionSpeech RecognitionSimilar Papers 제목 키워드 기반
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