SIGUL February 2022

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Fwd: Update for Event : Special Session on Low-Resource ASR Development
by Joseph Mariani 08 Feb '22

08 Feb '22

fyi, Joseph -------- Message transféré -------- Sujet : Update for Event : Special Session on Low-Resource ASR Development Date : Tue, 8 Feb 2022 10:21:32 +0000 De : ACL Member Portal <portal(a)aclweb.org> Pour : joseph.mariani(a)limsi.fr Greetings Mariani J Joseph, Call for Papers: Special Session on Low-Resource ASR Development at INTERSPEECH 2022 We invite submission of original results or studies on automatic speech recognition (ASR) technologies for low-resource languages to the preliminarily accepted Low-Resource ASR Special Session at INTERSPEECH 2022. The special session aims to bring together researchers from all sectors working on ASR (Automatic Speech Recognition) for low-resource languages and dialects to discuss the state of the art and future directions. It will allow for fruitful exchanges between participants in low-resource ASR challenges and evaluations and other researchers working on low-resource ASR development. One such challenge is the OpenASR Challenge series conducted by NIST (National Institute of Standards and Technology) in coordination with IARPA’s (Intelligence Advanced Research Projects Activity) MATERIAL (Machine Translation for English Retrieval of Information in Any Language) program. The most recent challenge, OpenASR21, offered an ASR test of 15 low resource languages for conversational telephone speech, with additional data genres and case-sensitive scoring for some of the languages. Another challenge is the Hindi ASR Challenge that was recently opened to evaluate regional variations of Hindi with the use of spontaneous telephone speech recordings made available by Gram Vaani, a social technology enterprise company. The regional variations of Hindi, together with spontaneity of speech, natural background, and transcriptions with varying degrees of accuracy due to crowd sourcing make it a unique corpus for automatic recognition of spontaneous telephone speech in low-resource regional variations of Hindi. A 1000 hours audio-only data (no transcription) is also released with this challenge to explore self-supervised training for such a low-resource framework. We invite contributions from the OpenASR21 Challenge participants, the MATERIAL performers, the Hindi ASR Challenge participants, and any other researchers with relevant work in the low-resource ASR problem space. Topics: Reports of results from tests of low-resource ASR, such as (but not limited to) the NIST/IARPA OpenASR21 Challenge, IARPA MATERIAL evaluations, and the Hindi ASR Challenge. Topics focused on aspects of challenges and solutions in low-resource settings, such as: Zero- or few-shot learning methods Transfer learning techniques Cross-lingual training techniques Use of pretrained models Factors influencing ASR performance (such as dialect, gender, genre, variations in training data amount, or casing) Any other topics focused on low-resource ASR challenges and solutions URL: https://www.nist.gov/itl/iad/mig/low-resource-asr-development-special-se... [1] Organizers: Peter Bell, University of Edinburgh Jayadev Billa, University of Southern California Information Sciences Institute Prasanta Ghosh, Indian Institute of Science, Bangalore William Hartmann, Raytheon BBN Technologies Kay Peterson, National Institute of Standards and Technology Aaditeshwar Seth, Indian Institute of Technology, Delhi Important dates: Initial paper submission deadline: March 21, 2022 Please see the Important Dates section of the INTERSPEECH 2022 Call for Papers for the most up-to-date paper submission, acceptance, and other relevant dates. Read more: https://www.aclweb.org/portal/content/special-session-low-resource-asr-deve… [1] https://www.nist.gov/itl/iad/mig/low-resource-asr-development-special-sessi… --- This is an automatic message from the ACL Member Portal. If you want to change your alert profile, please visit https://www.aclweb.org/portal/alerts/status and login to your account using your username (Mariani J Joseph). To unsubscribe from all ACL alerts and other announcements, visit https://www.aclweb.org/portal/unsubscribe/6539/502a7792e3fd0 -- Depuis le 1er janvier 2021, le LIMSI a fusionné avec le LRI et est devenu le LISN (Laboratoire Interdisciplinaire des Sciences du Numérique) Since January 1st 2021, LIMSI merged with the LRI lab and became the LISN (Interdisciplinary Computer Science Laboratory) - Joseph MARIANI Directeur de Recherche Émérite au CNRS LISN Rue John von Neumann Université Paris-Saclay Batiment 508 91405 ORSAY Cedex (France) Tel: +33 1 69 15 78 56 Email:Joseph.Mariani@limsi.fr Web:https://perso.limsi.fr/mariani/index Web IMMI:http://immi.cnrs.fr/

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SIGUL February 2022