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ISCApad #184 |
Friday, October 11, 2013 by Chris Wellekens |
7-1 | Special Issue of COMPUTER SPEECH AND LANGUAGE on Next Generation ParalinguisticsCall for Papers Special Issue of COMPUTER SPEECH AND LANGUAGE on Next Generation
Paralinguistics __________________________________
http://www.journals.elsevier.com/computer-speech-and-language/call-for-papers/next-generation-computational-paralinguistics/ Computational Paralinguistics recently reached a level of maturity allowing for their first real-life applications in interaction, coaching, media retrieval, robotics, surveillance, and manifold further
domains. In particular, an increasing level of realism is recently faced by coping with speaker
independent analysis of highly naturalistic data in narrow-bandwidth, noisy, or reverberated
conditions. At the same time, the richness of the range of speaker states and traits analysed
computationally is increasingly widening up. This includes in particular also the degree of
subjectivity faced with tasks such as perceived speaker personality, likability, or intelligibility,
to name a few. Both these aspects require additional experience on the interplay of states
and traits in speech, singing, and language. Further, with the integration in applications,
novel aspects arise such as efficiency, reliability, self-learning, mobility, multi-cultural and
multi-lingual aspects, handling groups of speaker or singers, standardisation, and user
experience with such systems. This Special Issue thus aims at shaping the Next Generation Computational Paralinguistics.
It will focus on technical issues for highly improved and reliable state and trait analysis in spoke
this topic. Original, previously unpublished submissions are encouraged within the following n,
sung, and written language and provide a forum for some of the very best experimental work
scope: +Analysis of States and Traits in Spoken, Sung, and Written Language +Subjectivity in Computational Paralinguistics (e.g., perceived states and traits) +Interdependence of States and Traits +Intelligibility of Language Varieties and Deviant Speech +Efficiency (low energy and memory consumption, fast adaptation, active learning, etc.) +Reliability (e.g., confidence measures, robustness against regulation and feigning, overlap) +Self-learning (unsupervised, partially supervised, reinforced, and deep learning) +Mobility (client/server distribution, package loss, coding artefacts, privacy preservation, etc.) +Multicultural and Multilingual Issues +Speaker / Singer Group Characterisation +Standardisation (output encoding, feature encoding, etc.) +Application (interaction, voice and writing coaching, retrieval, robotics, surveillance, etc.) +User Experience of Computational Paralinguistics Systems Important Dates __________________________________ Submission Deadline 1 April 2013 First Notification 1 July 2013 Final Version of Manuscripts 1 November 2013 Tentative Publication Date January 2014 Guest Editors __________________________________ Björn Schuller, Technische Universität München, Germany, schuller@IEEE.org Stefan Steidl, FAU, Germany, stefan.steidl@fau.de Anton Batliner, Technische Universität München, Germany, Anton.Batliner@lrz.uni-muenchen.de Alessandro Vinciarelli, University of Glasgow / IDIAP, UK, alessandro.vinciarelli@glasgow.ac.uk Felix Burkhardt, Deutsche Telekom AG, Germany, Felix.Burkhardt@telekom.de Rob van Son, University of Amsterdam / Netherlands Cancer Institute, NL , r.v.son@nki.nl Submission Procedure __________________________________ Prospective authors should follow the regular guidelines of the Computer Speech and Language Journal for electronic submission (http://ees.elsevier.com/csl). During submission
authors must select for this Special Issue (short name 'NextGen Paralinguistics').
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7-2 | CfP Special Issue of Neural Networks (Elsevier) on Affective and Cognitive Learning Systems for Big Social Data Analysis Special Issue of Neural Networks (Elsevier) on
Affective and Cognitive Learning Systems for Big Social Data Analysis
Guest Editors Amir Hussain*, University of Stirling, United Kingdom (ahu@cs.stir.ac.uk) Background and Motivation As the Web rapidly evolves, Web users are evolving with it. In an era of social connectedness, people are becoming more and more enthusiastic about interacting, sharing, and collaborating through social networks, online communities, blogs, Wikis, and other online collaborative media. In recent years, this collective intelligence has spread to many different areas, with particular focus on fields related to everyday life such as commerce, tourism, education, and health, causing the size of the Web to expand exponentially. The distillation of knowledge from such a large amount of unstructured information, however, is an extremely difficult task, as the contents of today's Web are perfectly suitable for human consumption, but remain hardly accessible to machines. The opportunity to capture the opinions of the general public about social events, political movements, company strategies, marketing campaigns, and product preferences has raised growing interest both within the scientific community, leading to many exciting open challenges, as well as in the business world, due to the remarkable benefits to be had from marketing and financial market prediction. Existing approaches to opinion mininig mainly rely on parts of text in which sentiment is explicitly expressed, e.g., through polarity terms or affect words (and their co-occurrence frequencies). However, opinions and sentiments are often conveyed implicitly through latent semantics, which make purely syntactical approaches ineffective. In this light, this Special Issue focuses on the introduction, presentation, and discussion of novel techniques that further develop and apply big data analysis tools and techniques for sentiment analysis. A key motivation for this Special Issue, in particular, is to explore the adoption of novel affective and cognitive learning systems to go beyond a mere word-level analysis of natural language text and provide novel concept-level tools and techniques that allow a more efficient passage from (unstructured) natural language to (structured) machine-processable data, in potentially any domain. Articles are thus invited in areas such as machine learning, weakly supervised learning, active learning, transfer learning, deep neural networks, novel neural and cognitive models, data mining, pattern recognition, knowledge-based systems, information retrieval, natural language processing, and big data computing. Topics include, but are not limited to: • Machine learning for big social data analysis The Special Issue also welcomes papers on specific application domains of big social data Timeframe Call for Papers out: April 2013 Composition and Review Procedures The Elsevier Neural Networks Special Issue on Affective and Cognitive Learning Systems for Big Social Data Analysis will consist of papers on novel methods and techniques that further develop and apply big data analysis tools and techniques in the context of opinion mining and sentiment analysis. Some papers may survey various aspects of the topic. The balance between these will be adjusted to maximize the issue's impact. All articles are expected to successfully negotiate the standard review procedures for Elsevier Neural Networks.
___________________________________________
Univ.-Prof. Dr.-Ing. habil. Björn W. Schuller
Head Institute for Sensor Systems University of Passau Passau / Germany
Head Machine Intelligence & Signal Processing Group Institute for Human-Machine Communication Technische Universität München Munich / Germany
CEO audEERING UG (haftungsbeschränkt) Gilching / Germany
Visiting Professor School of Computer Science and Technology Harbin Institute of Technology Harbin / P.R. China
Associate Institute for Information and Communication Technologies JOANNEUM RESEARCH Graz / Austria
Associate Centre Interfacultaire en Sciences Affectives Université de Genève Geneva / Switzerland
schuller@ieee.org http://www.schuller.it ___________________________________________
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7-3 | CFP: International Journal of Multimedia Information Retrieval -Special Issue on Cross-Media AnalysisCFP: International Journal of Multimedia Information Retrieval Special Issue on Cross-Media Analysis http://www.fortune.binghamton.edu/CFP_CMA_IJMIR2013.html Cross-media analysis is a new, emerging, and important research area in current multimedia research. Cross-media analysis exploits the data available on diverse sources of rich multimedia content simultaneously and synergistically. It is beneficial for many applications in data mining, causal inference, machine learning, multimedia, and public security. For more details, please see the special issue webpage above or contact one of the guest editors. Duedate for submissions: July 15th, 2013 Submissions Webpage: http://www.editorialmanager.com/mmir/default.asp Guest Editors: Zhongfei (Mark) Zhang SUNY Binghamton, USA zhongfei@cs.binghamton.edu Yueting Zhuang Zhejiang University, China yzhuang@cs.zju.edu.cn Ramesh Jain University of California, Irvine, USA jain@ics.uci.edu Jia-Yu (Tim) Pan Google, USA jypan@google.com
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7-4 | CfP Multimedia Tools and Applications, Journal, Springer Special Issue on 'Content Based Multimedia Indexing' Multimedia Tools and Applications, Journal, Springer Special Issue on 'Content Based Multimedia Indexing' CALL FOR PAPERS http://cbmi2013.mik.uni-pannon.hu/index.php/cfp ============================================================ Multimedia indexing systems aim at providing easy, fast and accurate access to large multimedia repositories. Research in Content-Based Multimedia Indexing covers a wide spectrum of topics in content analysis, content description, content adaptation and content retrieval. Various tools and techniques from different fields such as Data Indexing, Machine Learning, Pattern Recognition, and Human Computer Interaction have contributed to the success of multimedia systems. Although, there has been a significant progress in the field, we still face situations when the system shows limits in accuracy, generality and scalability. Hence, the goal of this special issue is to bring forward the recent advancements in content-based multimedia indexing. Topics of Interest ================== Topics of interest for the Special Issue include, but are not limited to: - Audio content extraction - Audio indexing (audio, speech, music) - Content-based search - Identification and tracking of semantic regions - Identification of semantic events - Large scale multimedia database management - Matching and similarity search - Metadata generation, coding and transformation, multi-modal fusion - Multimedia data mining - Multimedia interfaces, presentation and visualization tools - Multimedia recommendation - Multimedia retrieval (image, audio, video, ...) - Multi-modal and cross-modal indexing - Personalization and content adaptation - Summarization, browsing and organization of multimedia content - User interaction and relevance feedback - Visual content extraction - Visual indexing (image, video, graphics) Submission Details ================== All the papers should be full journal length versions and follow the guidelines set out by Multimedia Tools and Applications: http://www.springer.com/computer/information+systems/journal/11042. Manuscripts should be submitted online athttps://www.editorialmanager.com/mtap/ choosing 'Content Based Multimedia Indexing' as article type, no later than September 1st, 2013. When uploading your paper, please ensure that your manuscript is marked as being for this special issue. Information about the manuscript (title, full list of authors, corresponding author’s contact, abstract, and keywords) should also be sent to the corresponding editor Klaus Schoeffmann (ks@itec.uni-klu.ac.at). All the papers will be peer-reviewed following the MTAP reviewing procedures. Important Dates =============== Manuscript due: September 22nd, 2013 (extended)Notification: October 22nd, 2013 Publication date: First quarter 2014 Guest Editors ============= Klaus Schoeffmann, Klagenfurt University, Klagenfurt, Austria ks@itec.uni-klu.ac.at Tamás Szirányi, MTA SZTAKI, Budapest, Hungary sziranyi@sztaki.hu Jenny Benois-Pineau, University of Bordeaux 1, LABRI UMR 5800 Universities-Bordeaux-CNRS, France Jenny.benois@labri.fr Bernard Merialdo, EURECOM, Nice – Sophia Antipolis, France Bernard.Merialdo@eurecom.fr
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7-5 | CfP EURASIP Journal: Special Issue on Atypical Speech & Voices: Corpora, Classification, Coaching & Conversion EURASIP Journal on Audio, Speech, and Music Processing
Special Issue on Atypical Speech & Voices: Corpora, Classification, Coaching & Conversion
Call for Papers
With speech processing technology becoming more and more present in our every-day lives, it has become increasingly important to include all types of voices, speaking situations, and styles from all parts of our society, i.e., to move beyond the 'typical'.
Examples of such less typical patterns may include speaking while eating, during physical exercise, singing, as well as a wide range of pathological effects or speech generated by special aged groups (children, elderly).
In fact, recent advances in the field of Computational Paralinguistics allow for automatic recognition, analysis, and synthesis of an ever-increasing range of 'atypical' phenomena. At the same time, deeper analysis methods have opened doors to new assistive technologies, such as coaching systems, serious games, and tutoring systems, as well as diagnostic aids (e.g., for early detection of autism spectrum disorders, Alzheimer's or Parkinson's diseases). Tutoring systems, for example, have opened up new opportunities for voice professionals, such as public speakers, singers, and teachers, providing them with feedback on prosodic aspects, vibrato parameters, 'presence' or quality. Further, methods of speech/voice enhancement and conversion have enabled improvements in intelligibility of spoken content, as well as socio-emotional communication skills of e.g., speakers on the autism spectrum.
In this light and given the steadily growing research activities and their importance, we openly invite papers describing various aspects of analysis and synthesis of atypical speech and voices as well as their successful applications.
Submissions must not have been previously published and must have specific connection to audio, speech, and music processing.
The topics of particular interest will include, but are not limited to:
- Automatic Recognition of Atypical Speech & Voice Patterns
- Analysis of Atypical Speech, Singing & Voices
- Robustness in Automatic Speech Recognition against Atypical Phenomena
- Synthesis of Atypical Speech, Singing & Voices
- Enhancement and Conversion for Intelligibility Improvement of Atypical Speech & Voices
- Resources of Atypical Speech, Singing or Voice Patterns
- Multimodal Integration for Atypical Speech & Voice Processing (e.g., videolaryngoscopy, videokymography, fMRI, etc.)
- Tutoring Systems for Atypical Speech & Voice
- Serious Gaming Approaches in Atypical Speech & Voices
- Relationship Between Atypical Speech & Voices and Neurological Conditions
Submission Instructions:
Before submission authors should carefully read over the Instructions for Authors, which are located at asmp.eurasipjournals.com/authors/instructions. Prospective authors should submit an electronic copy of their complete manuscript through the SpringerOpen submission system at asmp.eurasipjournals.com/manuscript according to the submission schedule. They should choose the correct Special Issue in the 'sections' box upon submitting. In addition, they should specify the manuscript as a submission to the 'Special Issue on Atypical Speech & Voices' in the cover letter. All submissions will undergo initial screening by the Guest Editors for fit to the theme of the Special Issue and prospects for successfully negotiating the review process.
Guest Editors
Björn W. Schuller, Imperial College London, London, U.K. & TUM, Munich, Germany Email >bjoern.schuller@imperial.ac.uk
Tiago H. Falk, INRS-EMT, Montreal, Canada Email > falk@inrs.emt.ca
Vijay Parsa, University of Western Canada, London, Canada Email > parsa@nca.uwo.ca
Elmar Nöth, FAU Erlangen-Nuremberg, Germany & King Abdulaziz University, Jeddah, Saudi Arabia Email >noeth@cs.fau.de
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7-6 | CfP Eurasip journal: Special issue on Models of Speech-In search of better representationsManuscript due: Nov. 1, 2013 Journal: EURASIP Journal on Audio, Speech, and Music Processing Description: This special issue originates from a special session at the international conference Interspeech, which was held in September 2010 at Chiba, Japan. It will publish some key contributions presented at the conference describing different aspects of models of speech, from the analyisis or representation point of view. Topics of interest include: * Hidden Markov Models * Kernel Methods * Deep Neural Networks * Linear Predicitve Analysis Lead Guest Editor: * Hansjörg Mixdorff, Beuth University, Berlin, Germany Guest Editor: * Hideki Kawahara, Wakayama University, Wakayama, Japan For more information about this special issue, please visit: http://si.eurasip.org/issues/14/models-of-speech-in-search-of-better/
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7-7 | Eurasip Journal:CfP Special issue on Atypical Speech & Voices: Corpora, Classification, Coaching & ConversionManuscript due: Feb. 1, 2014 Journal: EURASIP Journal on Audio, Speech, and Music Processing Description: With speech processing technology becoming more and more present in our every-day lives, it has become increasingly important to include all types of voices, speaking situations, and styles from all parts of our society, i.e., to move beyond the “typical”. Examples of such less typical patterns may include speaking while eating, during physical exercise, singing, as well as a wide range of pathological effects or speech generated by special aged groups (children, elderly). In fact, recent advances in the field of Computational Paralinguistics allow for automatic recognition, analysis, and synthesis of an ever-increasing range of “atypical” phenomena. At the same time, deeper analysis methods have opened doors to new assistive technologies, such as coaching systems, serious games, and tutoring systems, as well as diagnostic aids (e.g., for early detection of autism spectrum disorders, Alzheimer’s or Parkinson’s diseases). Tutoring systems, for example, have opened up new opportunities for voice professionals, such as public speakers, singers, and teachers, providing them with feedback on prosodic aspects, vibrato parameters, “presence” or quality. Further, methods of speech/voice enhancement and conversion have enabled improvements in intelligibility of spoken content, as well as socio-emotional communication skills of e.g., speakers on the autism spectrum. In this light and given the steadily growing research activities and their importance, we openly invite papers describing various aspects of analysis and synthesis of atypical speech and voices as well as their successful applications. Submissions must not have been previously published and must have specific connection to audio, speech, and music processing. Topics of interest include: * Automatic Recognition of Atypical Speech & Voice Patterns * Analysis of Atypical Speech, Singing & Voices * Robustness in Automatic Speech Recognition against Atypical Phenomena * Synthesis of Atypical Speech, Singing & Voices * Enhancement and Conversion for Intelligibility Improvement of Atypical Speech & Voices * Resources of Atypical Speech, Singing or Voice Patterns * Multimodal Integration for Atypical Speech & Voice Processing (e.g., videolaryngoscopy, videokymography, fMRI, etc.) * Tutoring Systems for Atypical Speech & Voice * Serious Gaming Approaches in Atypical Speech & Voices * Relationship Between Atypical Speech & Voices and Neurological Conditions Lead Guest Editor: * Björn W. Schuller, Imperial College London, London, U.K. & TUM, Munich, Germany Guest Editors: * Tiago H. Falk, INRS-EMT, Montreal, Canada * Vijay Parsa, University of Western Canada, London, Canada * Elmar Nöth, FAU Erlangen-Nuremberg, Germany & King Abdulaziz University, Jeddah, Saudi Arabia For more information about this special issue, please visit: http://si.eurasip.org/issues/16/atypical-speech-voices-corpora-classification/
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