Supervised Single Channel Speech Enhancement Method Using UNET

Supervised Single Channel Speech Enhancement Method Using UNET

This paper proposes an innovative single-channel supervised speech enhancement (SE) method based on UNET, a convolutional neural network (CNN) architecture that expands on a few changes in the basic CNN architecture. In the training phase, short-time Fourier transform (STFT) is exploited on the nois...

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Bibliographic Details
Main Authors: Md. Nahid Hossain, Samiul Basir, Md. Shakhawat Hosen, A.O.M. Asaduzzaman, Md. Mojahidul Islam, Mohammad Alamgir Hossain, Md Shohidul Islam
Format: Article
Language:English
Published: MDPI AG 2023-07-01
Series:Electronics
Subjects:
speech enhancement (SE)
short-time Fourier transforms (STFT)
convolutional denoising auto encoder (CDAE)
dual-tree complex wavelet transform (DTCWT)
sparse non-negative matrix factorization (SNMF)
casual multi-head attention mechanism (CMAM)
Online Access:https://www.mdpi.com/2079-9292/12/14/3052

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https://www.mdpi.com/2079-9292/12/14/3052

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