Preparing your submissionA submission to the challenge consists of
- either an extended 2-page abstract or a full paper up to 6 pages (in case you addressed one track) or 8 pages (in case you addressed both tracks) describing your system and reporting its performance on the development and test sets
- the recognition output transcripts on these two sets (.mlf files)
Specific guidelinesCheck instructions for Track 1 and Track 2.
In the case when you used other data than provided in the training and development sets, please also report results which involve only those data provided in the training and development sets.
In the case when you used a different language model than provided in the baseline, please also report the results of your system with the provided baseline language model.
In the case when your system can be split into a front end and a back end and the latter differs from the provided baseline back end, you should also report the results of
- the baseline back-end system trained on denoised training data obtained with your own front end
- one of the provided pre-trained baseline back-end systems for clean, reverberated or noisy data (the best model among these is enough), only using your own front end to denoise the test data