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ISCApad Archive  »  2020  »  ISCApad #267  »  Journals  »  Special issue of Neural Networks on Advances in Deep Learning Based Speech Processing (Updated)

ISCApad #267

Thursday, September 10, 2020 by Chris Wellekens

7-10 Special issue of Neural Networks on Advances in Deep Learning Based Speech Processing (Updated)
Special issue on
Advances in Deep Learning Based Speech Processing

Extended deadline: August 30, 2020

Earlier submissions will be handled as they come. Accepted manuscripts will be published without waiting for later submissions.

Deep learning has triggered a revolution in speech processing. The revolution started from the successful application of deep neural networks to automatic speech recognition, and quickly spread to other topics of speech processing, including speech analysis, speech denoising and separation, speaker and language recognition, speech synthesis, and spoken language understanding. This tremendous success has been achieved thanks to the advances in neural network technologies as well as the explosion of speech data and fast development of computing power.

Despite this success, deep learning based speech processing still faces many challenges for real-world wide deployment. For example, when the distance between a speaker and a microphone array is larger than 10 meters, the word error rate of a speech recognizer may be as high as over 50%; end-to-end deep learning based speech processing systems have shown potential advantages over hybrid systems, however, they require large-scale labelled speech data; deep learning based speech synthesis has been highly competitive with human-sounding speech and much better than traditional methods, however, the models are not stable, lack controllability and are still too large and slow to be deployed onto mobile and IoT devices.

Therefore, new methods and algorithms in deep learning and speech processing are needed to tackle the above challenges, as well as to yield novel insights into new directions and applications.

This special issue aims to accelerate research progress by providing a forum for researchers and practitioners to present their latest contributions that advance theoretical and practical aspects of deep learning based speech processing techniques. The special issue will feature theoretical articles with novel new insights, creative solutions to key research challenges, and state-of-the-art speech processing algorithms/systems that demonstrate competitive performance with potential industrial impacts. The ideas addressing emerging problems and directions are also welcome.


Topics of interest for this special issue include, but are not limited to:
?   Speaker separation
?   Speech denoising
?   Speech recognition
?   Speaker and language recognition
?   Speech synthesis
?   Audio and speech analysis
?   Multimodal speech processing
Submission instructions: 
Prospective authors should follow the standard author instructions for Neural Networks, and submit manuscripts online at
Authors should select ?VSI: Speech Based on DL' when they reach the 'Article Type' step and the 'Request Editor' step in the submission process.

Important dates: 
June 30, 2020 - Submission deadline
September 30, 2020 - First decision notification
November 30, 2020 - Revised version deadline
December 31, 2020 - Final decision notification
March, 2021 - Publication
Guest Editors: 

Xiao-Lei Zhang, Northwestern Polytechnical University, China
Lei Xie, Northwestern Polytechnical University, China
Eric Fosler-Lussier, Ohio State University, USA
Emmanuel Vincent, Inria, France

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