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Participants must train a model to predict speech features from linguistic features (or, to directly predict speech waveforms from linguistic features, as done in Wave Net), and then use that model to make predictions for a test set of previously-unseen linguistic features.Evaluation will be done by the organisers, using a listening test, as in the main challenge. We need to know your team name, the name of the main contact person, your affiliation, and contact details including email address, postal address and phone number.We therefore propose a spin-off challenge that does not involve these speech-specific tasks, and allows participants to concentrate on the acoustic modeling task, framed as a straightforward ML problem, with a fixed data set.

The second part of the challenge is novel and is designed to be accessible to the wider machine learning community; it comprises two spoke tasks (2017-ES-ES2) Speech synthesis as a machine learning problem ---exploring new types of acoustic models In the HMM era, by taking a unified view of both Automatic Speech Recognition (ASR) and Text-to-Speech (TTS), it was possible to develop various types of new ASR and TTS techniques, e.g., cross-lingual speaker adaptation, adaptive training for TTS, use of prosody in ASR, etc.

Game director Jeff Kaplan and the Overwatch team have been more open than most development teams about what they’re working on, specifically under the caveat that plans do change, delays can happen, better ideas pop up, and life gets in the way.