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@aclweb.org>
Pour : joseph.mariani@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-development

[1] https://www.nist.gov/itl/iad/mig/low-resource-asr-development-special-session-interspeech-2022


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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/