Connectionists: Announcing the first COG-MHEAR Audio-visual Speech Enhancement Challenge (AVSEC) - as part of IEEE SLT 2022

[Amir Hussain]

Dear all  (please help share with colleagues)

We are pleased to announce the launch of *the* *first COG-MHEAR
Audio-visual Speech Enhancement Challenge (AVSEC)* -
http://challenge.cogmhear.org

Participants will work on a large dataset derived from TED talks to enhance
speech in extremely challenging noisy environments and with competing
speakers. The performance will be evaluated using human listening tests as
well as with objective measures. We hope that the Challenge will create a
benchmark for AVSEC research that will be useful for years to come. The
challenge data and development tools are now available - for details see
the challenge website: https://challenge.cogmhear.org/#/  and our github
repository: https://github.com/cogmhear/avse_challenge

AVSEC has been accepted as an official challenge at the *IEEE Spoken
Language Technology (SLT) Workshop* (https://slt2022.org/) to be held in
Doha, Qatar, 9-12 Jan 2023, where a special session will be run.

*Important Dates*

1st May 2022: Challenge website launch
31st May 2022: Release of the full toolset, training/development data and
baseline system
1 June 2022: Registration for challenge entrants opens
25th July 2022: Evaluation data released
1st Sept 2022: Submission deadline for evaluation (by objective and
subjective measures)
9th Jan 2023: Results announced at IEEE SLT 2022

*Background:*

Human performance in everyday noisy situations is known to be dependent
upon both aural and visual senses that are contextually combined by the
brain’s multi-level integration strategies. The multimodal nature of speech
is well established, with listeners known to unconsciously lip-read to
improve the intelligibility of speech in a real noisy environment. It has
been shown that the visual aspect of speech has a potentially strong impact
on the ability of humans to focus their auditory attention on a particular
stimulus.

The aim of the first AVSEC is to bring together the wider computer vision,
hearing and speech research communities to explore novel approaches to
multimodal speech-in-noise processing. Both raw and pre-processed AV
datasets – derived from TED talk videos – will be made available to
participants for training and development of audio-visual models to perform
speech enhancement and speaker separation at SNR levels that will be
significantly more challenging than those typically used in audio-only
scenarios. Baseline neural network models and a training recipe will be
provided.

In addition to participation at IEEE SLT, Challenge participants will be
invited to contribute to a Journal Special Issue on the topic of
Audio-Visual Speech Enhancement that will be announced early next year.

*Further information*:

If you are interested in participating and wish to receive further
information, please sign up here:
https://challenge.cogmhear.org/#/getting-started/register

If you have questions, contact us directly at: cogmhear at napier.ac.uk

*Organising Team*:

Amir Hussain, Edinburgh Napier University, UK (co-Chair)
Peter Bell, University of Edinburgh, UK (co-Chair)
Mandar Gogate, Edinburgh Napier University, UK
Cassia Valentini Botinhao, University of Edinburgh, UK
Kia Dashtipour, Edinburgh Napier University, UK
Lorena Aldana, University of Edinburgh, UK

Evaluation Panel Chair: John Hansen, University of Texas in Dallas, USA
Scientific Committee Chair: Michael Akeroyd, University of Nottingham, UK
Industry co-ordinator: Peter Derleth, Sonova AG

Funded by the UK Engineering and Physical Sciences Research Council (EPSRC)
programme grant: COG-MHEAR (http://cogmhear.org )

Supported by RNID (formerly Action on Hearing Loss), Deaf Scotland, Sonova
AG

--
Professor Amir Hussain
School of Computing,
Edinburgh Napier University, Scotland, UK
E-mail: A.Hussain at napier.ac.uk
https://www.napier.ac.uk/people/amir-hussain

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