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ISCApad Archive  »  2020  »  ISCApad #268  »  Journals  »  CfP Computer, Speech and Language, Special Issue on Separation, 'Recognition, and Diarization of Conversational Speech'

ISCApad #268

Saturday, October 10, 2020 by Chris Wellekens

7-15 CfP Computer, Speech and Language, Special Issue on Separation, 'Recognition, and Diarization of Conversational Speech'
  
Call for papers
 
Computer Speech and Language
 
Special Issue on Separation, Recognition, and Diarization of Conversational Speech

https://www.journals.elsevier.com/computer-speech-and-language/call-for-papers/call-for-papers-computer-speech-and-language-special-issue

 
Submission deadline: December 15, 2020
 
 
While great advances have been made in conversational automatic speech recognition in recent years, several fundamental problems remain before the goal of a richly annotated transcript of speech and speakers can be realized. The current special issue invites papers to discuss the robustness of speech processing in everyday environments, i.e., real-world conditions with acoustic clutter, where the number and nature of the sound sources is unknown and changing over time.
 
Relevant research topics include (but are not limited to):
  • Speaker identification and diarization
  • Speaker localization and beamforming
  • Single- or multi-microphone enhancement and separation
  • Robust features and feature transforms
  • Robust acoustic and language modeling
  • Traditional or end-to-end robust speech recognition
  • Training schemes: data simulation and augmentation, semi-supervised training
  • Robust speaker and language recognition
  • Robust paralinguistics
  • Cross-environment or cross-dataset performance analysis
  • Environmental background noise modelling.
In addition to traditional research papers, the special issue also hopes to include descriptions of successful conversational speech recognition systems where the contribution is more in the implementation than the techniques themselves as well as successful applications of conversational speech recognition systems.

The recently concluded sixth CHiME challenge serves as a focus for discussion in this special issue. The challenge considered the problem of conversational speech recognition and diarization in everyday home environments from multiple distant microphone arrays. It used a resychronized version of the Dinner Party speech data featured in CHiME-5 and added a new joint diarization and ASR task. Papers reporting evaluation results on the CHiME-6 dataset or on other datasets are equally welcome.


Submission instructions

Manuscript submissions shall be made through: https://www.editorialmanager.com/YCSLA/.

The submission system will be open in November. When submitting your manuscript please select the article type ?VSI:SeparateRecognizeDiarize?. Please submit your manuscript before the submission deadline.

All submissions deemed suitable to be sent for peer review will be reviewed by at least two independent reviewers. Once your manuscript is accepted, it will go into production, and will be simultaneously published in the current regular issue and pulled into the online Special Issue. Articles from this Special Issue will appear in different regular issues of the journal, though they will be clearly marked and branded as Special Issue articles. Please see an example here: https://www.sciencedirect.com/journal/science-of-the-total-environment/special-issue/10SWS2W7VVV

Please ensure you read the Guide for Authors before writing your manuscript. The Guide for Authors and the link to submit your manuscript is available on the Journal?s homepage https://www.elsevier.com/locate/csl.


Important dates:
  • Submission opens: November 16, 2020
  • Submission deadline: December 15, 2020
  • Acceptance deadline: September 1, 2021
  • Expected publication date: November 1, 2021

Guest editors
  • Michael Mandel, Brooklyn College, CUNY
  • Jon Barker, University of Sheffield
  • Jun Du, University of Science and Technology of China
  • Leibny Paola Garcia, Johns Hopkins University
  • Emmanuel Vincent, Inria
  • Shinji Watanabe, Johns Hopkins University

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