... ( 6 ) , 841–847 . doi : 10.100711701-020-01058-7 PMID : 32088836 Cardenas - Trowers , O. , Kjellsson , K. , & Hatch , K. ( 2018 ) . Ergonomics : Making the OR a comfortable place . International Urogynecology Journal and Pelvic Floor ...

In recent years, there has been a significant increase in the popularity of voice-enabled technologies which use human speech as the primary interface with machines.

This book covers the state-of-the-art in deep neural-network-based methods for noise robustness in distant speech recognition applications.

In this work, a multi-level acoustic modeling framework is proposed to address both the data sparsity problem and the quantization effect.

To compensate for the deviation between training and test conditions, we investigate a graph-based semi-supervised learning approach to acoustic modeling in automatic speech recognition.

To model the acoustics of a large vocabulary well while staying within a reasonable memory capacity, most speech recognition systems use phonetic models to share parameters across different words in the vocabulary.