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Deep learning reinvents the hearing aid

Type: Journal Paper

Author : DeLiang Wang

Year: 2017

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Investigation of Speech Separation as a Front-End for Noise Robust Speech Recognition

Type: Journal Paper

Author : Arun Narayanan; DeLiang Wang

Year: 2014

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The role of binary mask patterns in automatic speech recognition in background noise

Type: Journal Paper

Author : Narayanan, Arun; Wang, DeLiang

Publisher: American Institute of Physics

Year: 2013

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Image Segmentation Based on Oscillatory Correlation

Type: Journal Paper

Author : DeLiang Wang; David Terman

Year: 1997

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Neural networks for supervised pitch tracking in noise

Type: Conference Paper

Author : Kun Han , DeLiang Wang

Publisher: IEEE

Year: 2014

A structure-preserving training target for supervised speech separation

Type: Conference Paper

Author : Yuxuan Wang , DeLiang Wang

Publisher: IEEE

Year: 2014

Joint noise adaptive training for robust automatic speech recognition

Type: Conference Paper

Author : Narayanan, A. , DeLiang Wang

Publisher: IEEE

Year: 2014

Ideal ratio mask estimation using deep neural networks for robust speech recognition

Type: Journal Paper

Author : Arun Narayanan; DeLiang Wang

Year: 2013

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A structure-preserving training target for supervised speech separation

Type: Journal Paper

Author : Yuxuan Wang; DeLiang Wang

Year: 2014

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Towards Polyoxometalate-Integrated Nanosystems

Type: Journal Paper

Author : De-Liang Long; Leroy Cronin

Year: 2006

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Search

Deep learning reinvents the hearing aid

Investigation of Speech Separation as a Front-End for Noise Robust Speech Recognition

The role of binary mask patterns in automatic speech recognition in background noise

Image Segmentation Based on Oscillatory Correlation

Neural networks for supervised pitch tracking in noise

A structure-preserving training target for supervised speech separation

Joint noise adaptive training for robust automatic speech recognition

Ideal ratio mask estimation using deep neural networks for robust speech recognition

A structure-preserving training target for supervised speech separation

Towards Polyoxometalate-Integrated Nanosystems

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Deep learning reinvents the hearing aid

Investigation of Speech Separation as a Front-End for Noise Robust Speech Recognition

The role of binary mask patterns in automatic speech recognition in background noise

Image Segmentation Based on Oscillatory Correlation

Neural networks for supervised pitch tracking in noise

A structure-preserving training target for supervised speech separation

Joint noise adaptive training for robust automatic speech recognition

Ideal ratio mask estimation using deep neural networks for robust speech recognition

A structure-preserving training target for supervised speech separation

Towards Polyoxometalate-Integrated Nanosystems