[AUDITORY] CFP: Special Issue on Advances in Deep Learning Based Speech Processing

[DeLiang Wang <dwang@xxxxxxxxxxxxxxxxxx>]

Neural Networks Special issue Call for Papers:

*Advances in Deep Learning Based Speech Processing
*
https://www.journals.elsevier.com/neural-networks/call-for-papers/advances-in-deep-learning 

*
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*Deadline: June 30, 2020*

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 
https://www.editorialmanager.com/neunet/default.aspx 
<https://urldefense.com/v3/__https://www.editorialmanager.com/neunet/default.aspx__;!!KGKeukY!hyw14JfC_4VzymjJoHB5DKVZlDryYvR-avb5pEOk0U0nWB7HJqhdmcBfaCz5UYwN9lnTRA$>.
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