International audienceWe present the Zero Resource Speech Challenge 2019, which proposes to build a speech synthesizer without any text or pho-netic labels: hence, TTS without T (text-to-speech without text). We provide raw audio for a target voice in an unknown language (the Voice dataset), but no alignment, text or labels. Participants must discover subword units in an unsupervised way (using the Unit Discovery dataset) and align them to the voice recordings in a way that works best for the purpose of synthesizing novel utterances from novel speakers, similar to the target speaker's voice. We describe the metrics used for evaluation , a baseline system consisting of unsupervised subword unit discovery plus a standard TTS system, and a top...
We summarize the accomplishments of a multi-disciplinary workshop exploring the computational and sc...
We summarize the accomplishments of a multi-disciplinary workshop exploring the computational and sc...
We summarize the accomplishments of a multi-disciplinary work-shop exploring the computational and s...
International audienceWe present the Zero Resource Speech Challenge 2019, which proposes to build a ...
AbstractThis paper reports on the results of the Zero Resource Speech Challenge 2015, the first unif...
Submitted to Interspeech 2021. arXiv admin note: text overlap with arXiv:2011.11588International aud...
International audienceWe present the Zero Resource Speech Challenge 2020, which aims at learning spe...
The Interspeech 2015 Zero Resource Speech Challenge aims at discovering subword and word units from ...
International audienceRecent progress in self-supervised or unsupervised machine learning has opened...
International audienceWe describe a new challenge aimed at discovering subword and word units from r...
14 pages, including references and supplementary materialInternational audienceWe introduce a new un...
Zero resource speech processing refers to a scenario where no or minimal transcribed data is availab...
International audienceWe introduce Generative Spoken Language Modeling, the task of learning the aco...
Zero-shot text-to-speech (TTS) synthesis aims to clone any unseen speaker's voice without adaptation...
Zero resource speech processing refers to techniques which do not require manually transcribed spee...
We summarize the accomplishments of a multi-disciplinary workshop exploring the computational and sc...
We summarize the accomplishments of a multi-disciplinary workshop exploring the computational and sc...
We summarize the accomplishments of a multi-disciplinary work-shop exploring the computational and s...
International audienceWe present the Zero Resource Speech Challenge 2019, which proposes to build a ...
AbstractThis paper reports on the results of the Zero Resource Speech Challenge 2015, the first unif...
Submitted to Interspeech 2021. arXiv admin note: text overlap with arXiv:2011.11588International aud...
International audienceWe present the Zero Resource Speech Challenge 2020, which aims at learning spe...
The Interspeech 2015 Zero Resource Speech Challenge aims at discovering subword and word units from ...
International audienceRecent progress in self-supervised or unsupervised machine learning has opened...
International audienceWe describe a new challenge aimed at discovering subword and word units from r...
14 pages, including references and supplementary materialInternational audienceWe introduce a new un...
Zero resource speech processing refers to a scenario where no or minimal transcribed data is availab...
International audienceWe introduce Generative Spoken Language Modeling, the task of learning the aco...
Zero-shot text-to-speech (TTS) synthesis aims to clone any unseen speaker's voice without adaptation...
Zero resource speech processing refers to techniques which do not require manually transcribed spee...
We summarize the accomplishments of a multi-disciplinary workshop exploring the computational and sc...
We summarize the accomplishments of a multi-disciplinary workshop exploring the computational and sc...
We summarize the accomplishments of a multi-disciplinary work-shop exploring the computational and s...