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Enhanced Zero-Resource Speech Challenge 2021: Language Modelling from Speech and Images + Q&A
Ewan Dunbar · Alejandrina Cristia · Okko Räsänen · Bertrand Higy · Marvin Lavechin · Grzegorz Chrupała · Afra Alishahi · Chen Yu · Maureen De Seyssel · Tu Anh Nguyen · Mathieu Bernard · Nicolas Hamilakis · Emmanuel Dupoux

Fri Dec 10 02:25 AM -- 02:45 AM (PST) @
in Competition Track Day 4: Overviews + Breakout Sessions »
Event URL: https://zerospeech.com/2021/ »

The Zero Resource Speech Challenge is a series that has been running since 2015, which aims to advance research in unsupervised training of speech and dialogue tools, with an application in speech technology for under-resourced languages. This year, we are running an "enhanced" version of the newest challenge task, language modelling from speech. This task asks participants to learn a sequential model that can assign probabilities to sequences---like a typical language model---but which must be trained, and operate, without any text. Assessing and improving on our ability to build such a model is critical to expanding applications such as speech recognition and machine translation to languages without textual resources. The "enhanced" version makes two modifications: it expands the call for submissions to the "high GPU budget" category, encouraging very large models in addition to the smaller, "lower-budget" ones experimented with up to now; and it includes a new, experimental "multi-modal" track, which allows participants to assess the performance of models that include images in training, in addition to audio. Baseline models are already prepared and evaluated for the high-budget and multi-modal settings.

Author Information

Ewan Dunbar (University of Toronto)
Alejandrina Cristia (École Normale Supérieure)
Okko Räsänen (Tampere University)
Bertrand Higy (Tilburg University)
Marvin Lavechin (École Normale Supérieure)
Grzegorz Chrupała (Tilburg University)
Afra Alishahi (Tilburg University)
Chen Yu (Indiana University)
Maureen De Seyssel (École Normale Supérieure)
Tu Anh Nguyen (INRIA, Paris, France)
Mathieu Bernard (Cognitive Machine Learning, EHESS, ENS-PSL University, CNRS, INRIA)
Nicolas Hamilakis (Cognitive Machine Learning, EHESS, ENS-PSL University, CNRS, INRIA)
Emmanuel Dupoux (Facebook)

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