Whispered Speech Recognition Using Deep Denoising Autoencoder and Inverse Filtering

Due to the profound differences between acoustic characteristics of neutral and whispered speech, the performance of traditional automatic speech recognition (ASR) systems trained on neutral speech degrades significantly when whisper is applied. In order to deeply analyze this mismatched train/test...

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Vydané v:	IEEE/ACM transactions on audio, speech, and language processing Ročník 25; číslo 12; s. 2313 - 2322
Hlavní autori:	Grozdic, Dorde T., Jovicic, Slobodan T.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	IEEE 01.12.2017
Predmet:	Automatic speech recognition Biology Character recognition deep denoising autoencoder Encoding Inverse filtering Mel frequency cepstral coefficient Noise levels Speech recognition Teager-energy operator whispered speech recognition
ISSN:	2329-9290, 2329-9304
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