Manuscript 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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Manuscript 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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Call for Papers - Special Issue of ACM Transactions on Accessible Computing (TACCESS) On

Speech and Language Interaction for Daily Assistive Technology

Guest Editors: François Portet, Frank Rudzicz, Jan Alexandersson, Heidi Christensen

Assistive technologies (AT) allow individuals with disabilities to do things that would otherwise be difficult or impossible. Many assistive technologies involve providing universal access, such as modifications to televisions or telephones to make them accessible to those with vision or hearing impairments. An important sub-discipline within this community is Augmentative and Alternative Communication (AAC), which has its focus on communication technologies for those with impairments that interfere with some aspect of human communication, including spoken or written modalities. Another important sub-discipline is Ambient Assisted Living (AAL) which facilitates independent living; these technologies break down the barriers faced by people with physical or cognitive impairments and support their relatives and caregivers. These technologies are expected to improve quality-of-life of users and promote independence, accessibility, learning, and social connectivity.

Speech and natural language processing (NLP) can be used in AT/AAC in a variety of ways including, improving the intelligibility of unintelligible speech, and providing communicative assistance for frail individuals or those with severe motor impairments. The range of applications and technologies in AAL that can rely on speech and NLP technologies is very large, and the number of individuals actively working within these research communities is growing, as evidenced by the successful INTERSPEECH 2013 satellite workshop on Speech and Language Processing for Assistive Technologies (SLPAT). In particular, one of the greatest challenges in AAL is to design smart spaces (e.g., at home, work, hospital) and intelligent companions that anticipate user needs and enable them to interact with and in their daily environment and provide ways to communicate with others. This technology can benefit each of visually-, physically-, speech- or cognitively- impaired persons.

Topics of interest for submission to this special issue include (but are not limited to):

• Speech, natural language and multimodal interfaces designed for people with physical or cognitive impairments
• Applications of speech and NLP technology (automatic speech recognition, synthesis, dialogue, natural language generation) for AT applications
• Novel modeling and machine learning approaches for AT applications
• Long-term adaptation of speech/NLP based AT system to user's change
• User studies, overview of speech/NLP technology for AT: understanding the user's needs and future speech and language based technologies.
• Understanding, modeling and recognition of aged or disordered speech
• Speech analysis and diagnosis: automatic recognition and detection of speech pathologies and speech capability loss
• Speech-based distress recognition
• Automated processing of symbol languages, sign language and nonverbal communication including translation systems.
• Text and audio processing for improved comprehension and intelligibility, e.g., sentence simplification or text-to-speech
• Evaluation methodology of systems and components in the lab and in the wild.
• Resources; corpora and annotation schemes
• Other topics in AAC, AAL, and AT

Submission process

Contributions must not have been previously published or be under consideration for publication elsewhere, although substantial extensions of conference or workshop papers will be considered. as long as they adhere to ACM's minimum standards regarding prior publication (http://www.acm.org/pubs/sim_submissions.html). Studies involving experimentations with real target users will be appreciated. All submissions have to be prepared according to the Guide for Authors as published in the Journal website at http://www.rit.edu/gccis/taccess/. 

Submissions should follow the journal's suggested writing format (http://www.gccis.rit.edu/taccess/authors.html) and should be submitted through Manuscript Central http://mc.manuscriptcentral.com/taccess , indicating that the paper is intended for the Special Issue. All papers will be subject to the peer review process and final decisions regarding publication will be based on this review.

Important dates:

◦   Full paper submission: 31^st March 2014

◦   Response to authors: 30^th June 2014

◦   Revised submission deadline: 31^st August 2014

◦   Notification of acceptance: 31^st October 2014

◦   Final manuscripts due: 30^th November 2014

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Aims and Scope
With the rapid advancement in microelectronics and parallel computing, significant computational power is nowadays readily available in ever smaller battery-operated consumer electronics devices. This has paved the way for applications such as active noise cancellation (ANC) headphones, hearing protectors, communication headsets, 3-D glasses, to name a few. In addition, hearing aids have also experienced large advances in electronics and functionality. To a large extent this rapid development can be attributed to the popularity of mobile phones, as these devices are no longer used merely as a communication tool but are multi-media and gaming platforms. Accordingly they require sophisticated processing for augmented reality in which the virtual listening world can be combined conveniently with situational acoustical awareness. The same can be said for assistive listening devices (ALDs), including hearing aids, personal sound amplification devices, and related audio capture accessories. Here the challenge is to render the sound as accessible as possible in order to provide hearing support in challenging acoustical situations. All aforementioned applications are underpinned by fundamental signal processing problems related to sound capture and sound rendering. On the one hand, for sound capture problems such as sensor technology (microphones, accelerometers etc.), acoustic scene analysis, audio signal enhancement, noise suppression with single and multiple sensors, feedback suppression and dereverberation need to be considered. On the other hand, sound rendering involves problems such as active noise cancellation, loudspeaker equalization (for mimicking or adapting outer-ear characteristics), 3-D audio rendering, acoustic scene visualization, automatic mixing and psycho-acoustical processing.

This special issue focuses on technical challenges of assisted listening from a signal processing perspective. Prospective authors are invited to contribute tutorial and survey articles that articulate signal processing methodologies which are critical for applying assisted listening techniques to mobile phones and other communication devices. Of particular interest is the role of signal processing in combining multimedia content, voice communication and voice pick-up in various real-world settings.

Tutorial and survey papers are solicited on advances in signal processing that particularly apply to the following applications:

• Assistive listening devices, hearing aids and personal sound amplifiers
• Communication devices
• Hearing protection and active noise control
• Navigation systems

These can include the following suggested topics as they relate to the above applications:

Submission Process
Articles submitted to this special issue must contain significant relevance to advanced acoustic signal processing enabling assisted listening. All submissions will be peer reviewed according to the IEEE and Signal Processing Society guidelines for both publications. Submitted articles should not have been published or be under review elsewhere. Manuscripts should be submitted online at http://mc.manuscriptcentral.com/sps-ieee using the Manuscript Central interface. Submissions to this special issue of the IEEE SIGNAL PROCESSING MAGAZINE should have significant tutorial value. Prospective authors should consult the site http://www.signalprocessingsociety.org/publications/periodicals/spm/ for guidelines and information on paper submission.

Important Dates: Expected publication date for this special issue is March 2015.

Guest Editors
Sven Nordholm, Lead GE, Curtin University, Perth, Western Australia (s.nordholm@curtin.edu.au)
Walter Kellermann, Friedrich-Alexander University, Erlangen-Nuremberg, Germany (wk@lnt.de)
Simon Doclo, University of Oldenburg, Oldenburg, Germany (simon.doclo@uni-oldenburg.de)
Vesa Välimäki, Aalto University, Espoo, Finland (vesa.valimaki@alto.fi)
Shoji Makino, University of Tsukuba, Tsukuba, Japan (maki@tara.tsukuba.ac.jp)
John Hershey, Mitsubishi Electric Research Laboratories, Boston, USA (hershey@merl.com)

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