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ISCApad #270 |
| Friday, December 11, 2020 by Chris Wellekens |
7 Journals
| 7-1 | CfP IEEE JSTSP Special Issue on Tensor Decomposition for Signal Processing and Machine LearningCall for Papers
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Important Dates
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Call for Papers
IEEE JSTSP Special Issue on
Reconstruction of Audio from Incomplete
or Highly Degraded Observations
The restoration of audio content, in particular speech and music from degraded observations, is a challenging and long-standing problem in audio processing. In particular this holds for severe degradations and incomplete observations. Traditional restoration techniques are often not applicable or perform poorly in this case. The advent of sparse signal processing in the beginning of this century and, even more recently, of (deep) machine learning has opened wide new research and design opportunities for audio restoration, among many other signal processing problems. With the aid of such contemporary tools, researchers have recently been able to achieve unprecedented success in recovering or significantly improving quality of severely degraded audio. As the field advances very quickly, the potential for improvement, as well as exploration, is hardly exhausted.
Audio restoration addresses a large number of important degradation scenarios. Further, audio restoration can be performed with varied tools. The proposed issue will serve both as a comprehensive primer on the state-of-the-art, and a showcase of current developments within the field, targeting newcomers as well as already experienced researchers.
Topics of interest in this special issue include (but are not limited to):
- Restoration problems:
packet loss concealment; inpainting; declipping; dequantization; phase recovery; bandwidth extension; coding artifact removal; compressive sampling recovery; dynamic range decompression; reconstructing audio signals from features, - Methodological frameworks:
time-frequency representations; (non-)convex optimization; operator and dictionary learning; nonnegative matrix/tensor factorization; (end-to-end) artificial neural networks; generative networks (e.g., generative adversarial nets and variational autoencoders); graph signal processing; psychoacoustics.
Excellent articles that cannot be accommodated in the special issue will be automatically transferred (without re-submission) and considered for regular publication in IEEE/ACM TASLP.
This special issue encourages reproducible research: authors are invited to provide their code and data, to use available material for benchmarking (e.g. SMALL dataset), and to contribute by any means (e.g., high-quality datasets and code, challenges) to the sustainability, the reproducibility and the reliability of the research works in the proposed topics.
Accepted articles are immediately published as Early Access and do not wait until the entire special issue is closed.
Prospective authors should follow the instructions given on the IEEE JSTSP webpages and submit their manuscript to the web submission system.
Important Dates
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Manuscript submission: May 1, 2020 (Extended)
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Decision notification: July 1, 2020
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Revised manuscript due: August 1, 2020
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Second reviews completed: September 15, 2020
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Final manuscript due: November 1, 2020
Guest Editors
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Pavel Rajmic (Brno University of Technology, Czech Republic), rajmic@vutbr.cz, lead guest editor
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Valentin Emiya (Aix-Marseille University, France), valentin.emiya@univ-amu.fr
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Nicki Holighaus (Acoustics Research Institute, Austrian Academy of Sciences, Austria), nicki.holighaus@oeaw.ac.at
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Nancy Bertin (Univ Rennes, Inria, CNRS, IRISA, France), nancy.bertin@irisa.fr
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Alexey Ozerov (InterDigital, Cesson Sevigne, France), alexey.ozerov@interdigital.com
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CFP: Special Issue on ?Behavior and Usability Analysis for Multimodal User Interfaces? in JMUI
Joint analysis of different modalities of user inputs such as text, speech, voice, facial expressions, gesture, and physiological signals, is an important area of research, and highly beneficial in more natural and effective forms of intelligent human computer interaction. With the recent dramatic advances in machine learning, signal processing, computer vision, and natural language processing, variety of multimodal applications increases every day. Application areas include healthcare, autonomous driving, robotics, sports analytics, neuromarketing, psychological and physiological assessment, surveillance, gaming, and augmented/virtual reality. Consequently, in the era of intelligent systems, reliable interpretation of human behavior and detailed analysis of usability for multimodal user interfaces gain further importance.
We solicit contributions to a special issue of the Journal on Multimodal User Interfaces on ?Behavior and Usability Analysis for Multimodal User Interfaces.? For this special issue, we welcome technical and empirical studies that focus on (a) interpretation and modeling of behavioral patterns, and (b) analysis and assessment of usability for multimodal human computer interaction. The topics include, but are not restricted to:
- Usability analysis
- User-centered interaction
- Human activity analysis
- Social signal processing
- Facial expression and gesture recognition
- Face and body tracking
- Speech recognition and voice analysis
- Text analysis
- Psychological and physiological assessment
- Multimodal fusion
- Spatio-temporal dynamics of actions and behavior
- Benchmarking studies on novel databases
SUBMISSIONS:
Submissions must represent original material. Papers are accepted for review with the understanding that the same work has been neither submitted to, nor published in, another journal or conference. All manuscripts will undergo a rigorous review process. Please indicate in your cover letter that you are submitting to the special issue. The authors are required to follow the Submission Guidelines of the Journal on Multimodal User Interfaces:
https://www.springer.com/journal/12193/submission-guidelines
IMPORTANT DATES:
Deadline for paper submission: 10 May 2020
Notification of review outcome: 5 July 2020
Camera-ready version of accepted papers: 9 August 2020
Estimated publication date: Autumn 2020
EDITOR IN CHIEF:
Jean-Claude Martin, LIMSI/CNRS - University Paris South XI
GUEST EDITORS:
Hamdi Dibeklioglu, Bilkent University
Elif Surer, Middle East Technical University
Albert Ali Salah, Utrecht University
Thierry Dutoit, University of Mons
To submit a manuscript, visit https://www.springer.com/journal/12193
For more information contact:
Asst. Prof. Dr. Hamdi Dibeklioglu
Department of Computer Engineering,
Bilkent University
06800 Bilkent - Ankara, Turkey
phone: +90 (312) 290 1187
home: http://www.cs.bilkent.edu.tr/~dibeklioglu/
e-mail: dibeklioglu@cs.bilkent.edu.tr
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This special issue solicits papers describing advances in privacy protection for speech processing systems, including theoretical developments, algorithms or systems.
- formal models of speech privacy preservation,
- privacy-preserving speech feature extraction,
- privacy-driven speech deletion or obfuscation,
- privacy-driven voice conversion,
- privacy-driven speech synthesis and transformation,
- privacy-preserving decentralized learning of speech models,
- speech processing in the encrypted domain,
- open resources, e.g., datasets, software or hardware implementations, evaluation recipes, objective and subjective metrics.
Manuscript submissions shall be made through: https://www.editorialmanager.com/YCSLA/.
The submission system will be open early October. When submitting your manuscript please select the article type ?VSI: Voice Privacy?. 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.
January 8, 2021: Paper submission
May 7, 2021: First review
July 9, 2021: Revised submission
September 10, 2021: Final decision
October 8, 2021: Camera-ready submission
Natalia Tomashenko, Avignon Université
Junichi Yamagishi, National Institute of Informatics and University of Edinburgh
Nicholas Evans, EURECOM
Paris Smaragdis, University of Illinois at Urbana-Champaign
Jean-François Bonastre, Avignon Université
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Earlier submissions will be handled as they come. Accepted manuscripts will be published without waiting for later submissions.
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.
September 30, 2020 - First decision notification
November 30, 2020 - Revised version deadline
December 31, 2020 - Final decision notification
March, 2021 - Publication
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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Special issue on ' Machine Learning Applied to Music/Audio Signal Processing' in MDPI Electronics at
https://www.mdpi.com/si/51394
Dear Colleagues,
The applications of audio and music processing range from music discovery and recommendation systems over speech enhancement, audio event detection, and music transcription, to creative applications such as sound synthesis and morphing.
The last decade has seen a paradigm shift from expert-designed algorithms to data-driven approaches. Machine learning approaches, and Deep Neural Networks specifically, have been shown to outperform traditional approaches on a large variety of tasks including audio classification, source separation, enhancement, and content analysis. With data-driven approaches, however, came a set of new challenges. Two of these challenges are training data and interpretability. As supervised machine learning approaches increase in complexity, the increasing need for more annotated training data can often not be matched with available data. The lack of understanding of how data are modeled by neural networks can lead to unexpected results and open vulnerabilities for adversarial attacks.
The main aim of this Special Issue is to seek high-quality submissions that present novel data-driven methods for audio/music signal processing and analysis and address main challenges of applying machine learning to audio signals. Within the general area of audio and music information retrieval as well as audio and music processing, the topics of interest include, but are not limited to, the following:
- unsupervised and semi-supervised systems for audio/music processing and analysis
- machine learning methods for raw audio signal analysis and transformation
- approaches to understanding and controlling the behavior of audio processing systems such as visualization, auralization, or regularization methods
- generative systems for sound synthesis and transformation
- adversarial attacks and the identification of 'deepfakes' in audio and music
- audio and music style transfer methods
- audio recording and music production parameter estimation
- data collection methods, active learning, and interactive machine learning for data-driven approaches
Dr. Peter Knees
Dr. Alexander Lerch
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Aims and Scope
For over ten years, the scientific community has been witnessing a permanent rise in the number of modern feature-learning approaches for speech and voice analysis. Although those strategies have been placed at the forefront of current artificial intelligence research, uninterpretable models and high computational costs characterise their main drawbacks. Thus, the intention of this special issue is to attract the attention to the fact that, in many problems, handcrafted extraction may still provide prominent solutions with low computational costs and easy-to-interpret features.
Topics of Interest
The particular topics of interest are those focusing on handcrafted feature extraction approaches for speech and voice analysis. Applications include, but are not necessarily limited to:
• text-dependent, text-prompted and text-independent speaker identification and verification
• spoken word, limited-vocabulary and large-vocabulary speech recognition
• speech emotion identification
• speech characterisation
• voice activity detection
• idiom recognition
• speech pathology detection
• emerging applications, including coronavirus detection based on speech
Before submission, prospective authors should carefully read over the journal author guidelines before submitting the electronic copy of their complete manuscripts through the journal online submission system. Please choose 'VSI:SHFESVA' for the 'article type” during submission.
Important Dates
• submission deadline: July 30, 2020
• results from the first round of reviews: September 30, 2020
• revised papers due: October 15, 2020
• results from the second round of reviews: November 30, 2020
• re-revised papers due: December 30, 2020
• final decisions: January 30, 2021
Guest-editors
Prof. (Dr.) Rodrigo Capobianco Guido (guido@ieee.org), São Paulo State University (UNESP), Brazil
Prof. (Dr.) Hemant A. Patil ( ), Dhirubhai Ambani Institute of Information and Communication Technology (DA-IICT), Gandhinagar, Gujarat, India.
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- Multi-domain task-completion track addresses the end-to-end response generation problems in multi-domain task completion and cross-domain adaptation scenarios.
- NOESIS II: Predicting Responses, Identifying Success, and Managing Complexity in Task-Oriented Dialogue explores a response selection task extending the first NOESIS track in DSTC7 and offers two additional subtasks for identifying task success and disentangling conversations.
- Audio visual scene-aware dialog track is another follow-up track of DSTC7 which aims to generate dialog responses using multi-modal information given in an input video.
- Schema-guided dialog state tracking revisits dialog state tracking problems in a practical setting associated with a large number of services/APIs required to build virtual assistants in practice.
- Manuscript submission date: August 15, 2020
- First Review Completed: October 15, 2020
- Revised Manuscript Due: November 30, 2020
- Second Review Completed: January 15, 2021
- Final Manuscript Due: February 28, 2021
- Expected publication date: May 2021
- Seokhwan Kim, Amazon Alexa AI, USA
- Hannes Schulz, Microsoft Research Montreal, Canada
- Chulaka Gunasekara, IBM Research AI, USA
- Chiori Hori, Mitsubishi Electric Research Laboratories (MERL), USA
- Abhinav Rastogi, Google Research, USA
- Luis Fernando D'Haro, Universidad Politécnica de Madrid (UPM), Spain
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Call for submission: http://tal-62-1.sciencesconf.org/ (page soon available)
TAL Journal: regular issue
2021 Volume 62-1
Editors : Cécile Fabre, Emmanuel Morin, Sophie Rosset and Pascale Sébillot
Deadline for submission: 12/15/2020
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TOPICS
The TAL journal launches a call for papers for an open issue of the journal. We invite papers in any field of natural language processing, including:
- lexicon, syntax, semantics, discourse and pragmatics;
- morphology, phonology and phonetics;
- spoken and written language analysis and generation;
- logical, symbolic and statistical models of language;
- information extraction and text mining;
- multilingual processing, machine translation and translation tools;
- natural language interfaces and dialogue systems;
- multimodal interfaces with language components;
- language tools and resources;
- system evaluation;
- terminology, knowledge acquisition from texts;
- information retrieval;
- corpus linguistics;
- use of NLP tools for linguistic modeling;
- computer assisted language learning;
- applications of natural language processing.
Whatever the topic, papers must stress the natural language processing aspects.
'Position statement' or 'State of the art' papers are welcome.
LANGUAGE
Manuscripts may be submitted in English or French. Submissions in English are accepted only if one of the co-authors is a non French-speaking person.
THE JOURNAL
TAL (http://www.atala.org/revuetal - Traitement Automatique des Langues / Natural Language Processing) is an international journal published by ATALA (French Association for Natural Language Processing) since 1960 with the support of CNRS (National Centre for Scientific Research). It has moved to an electronic mode of publication.
IMPORTANT DATES
Deadline for submission: 12/15/2020
Notification to authors after first review: 03/15/2021
Notification to authors after second review: 05/31/2021
Publication: October, 2021
FORMAT SUBMISSION
Papers should strictly be between 20 and 25 pages long.
TAL performs double-blind review: it is thus necessary to anonymise the manuscript and the name of the pdf file and to avoid self references.
Style sheets are available for download on the Web site of the journal (http://www.atala.org/content/instructions-aux-auteurs-feuilles-de-style-0).
Authors who intend to submit a paper are encouraged to upload your contribution via the menu 'Paper submission' (PDF format). To do so, you will need to have an account on the sciencesconf platform. To create an account, go to the site http://www.sciencesconf.org and click on 'create account' next to the 'Connect' button at the top of the page. To submit, come back to the page (soon available) http://tal-62-1.sciencesconf.org/, connect to you account and upload your submission.
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The call is open for about a year now and articles are published continuously.
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Call for Papers: Data, Replicability and Reproducibility in Linguistics
For scientific theories based on empirical data, reproducibility and replicability are central principles, for at least two reasons. First, unless we accept that scientific theories rest on the authority of a small number of researchers, empirical studies should be reproducible, in the sense that their methods and procedures should be carefully documented and relevant data should be made available so that other researchers to conduct the same study and obtain the same results. Second, for empirical results to provide a solid basis for scientific theorisation, they should also be replicable in the sense that most attempts to reproduce the original study using similar data and methods would produce results similar to those presented in the original study.
Although science depends on replicability and reproducibility, works aimed at replicating impact studies are quite rare due to the emphasis academia places on novelty: editors and reviewers of journals usually value original research higher than replication studies. Likewise, editors and reviewers value the presentation of empirical data (and significant findings) higher than, for example, the presentation of raw data such as annotated speech corpora and similar documentations.
We are organizing a special issue for Revista da Abralin whose objective is to gather articles that contribute to the central principle of replication / reproduction of experimental studies in the area of linguistics. The focus should be on impact studies, i.e. studies that were or still are frequently cited well beyond the authors' own citation circles, not necessarily only those studies that directly led to influential theories).
Three types of submissions are welcome.
- Submissions that focus entirely on replication/reproduction. When designing such studies, authors are encouraged to work in collaboration with those author(s) of the original study to ensure that replication follows as closely as possible the original methods.
- Submissions that replicate a key aspect of a previous study and then add an own original piece of work on top, for example, in order to explain why the previous results could not be replicated or in order to advance or substantiate the previous results. This can be done by applying a different (measuring) method, by using different speaker or listener samples (e.g., with respect to language, age, or gender), or by following up on one of the open questions raised by the author(s) in the previous study.
- Submissions that present a speech, gesture, or language-data corpus and that make this resource available to the linguistics community.
All papers submitted to this special issue of Revista da Abralin should be pre-registered on the Open Science Framework website (https://osf.io/).
Submission deadline: December 31, 2020
Submission link: http://revista.abralin.org/index.php/abralin/submission/wizard
Author Guidelines and Submission Preparation Checklist are available here: http://revista.abralin.org/index.php/abralin/about/submissions
Guest Editors:
Miguel Oliveira, Jr. (Universidade Federal de Alagoas)
Oliver Niebuhr (University of Southern Denmark)
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This special issue solicits papers describing advances in privacy protection for speech processing systems, including theoretical developments, algorithms or systems.
- formal models of speech privacy preservation,
- privacy-preserving speech feature extraction,
- privacy-driven speech deletion or obfuscation,
- privacy-driven voice conversion,
- privacy-driven speech synthesis and transformation,
- privacy-preserving decentralized learning of speech models,
- speech processing in the encrypted domain,
- open resources, e.g., datasets, software or hardware implementations, evaluation recipes, objective and subjective metrics.
Manuscript submissions shall be made through: https://www.editorialmanager.com/YCSLA/.
The submission system will be open early October. When submitting your manuscript please select the article type ?VSI: Voice Privacy?. 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.
January 8, 2021: Paper submission
May 7, 2021: First review
July 9, 2021: Revised submission
September 10, 2021: Final decision
October 8, 2021: Camera-ready submission
Natalia Tomashenko, Avignon Université
Junichi Yamagishi, National Institute of Informatics and University of Edinburgh
Nicholas Evans, EURECOM
Paris Smaragdis, University of Illinois at Urbana-Champaign
Jean-François Bonastre, Avignon Université
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- 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.
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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Faculdade de Letras da Universidade de Lisboa | School of Arts and Humanities
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