Advances in all-neural speech recognition

This paper advances the design of CTC-based all-neural (or end-to-end) speech recognizers. We propose a novel symbol inventory, and a novel iterated-CTC method in which a second system is used to transform a noisy initial output into a cleaner version. We present a number of stabilization and initia...

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Bibliographic Details
Published in2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) pp. 4805 - 4809
Main Authors Zweig, Geoffrey, Chengzhu Yu, Droppo, Jasha, Stolcke, Andreas
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.03.2017
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