5 citations · 9 across the 5 of their papers we have counts for
7 papers · 1 filter
The Zero Resource Speech Challenge 2020: Discovering discrete subword and word units
Ewan Dunbar, Julien Karadayi, Mathieu Bernard +6
We present the Zero Resource Speech Challenge 2020, which aims at learning speech representations from raw audio signals without any labels. It combines the data sets and metrics f…
The Zero Resource Speech Challenge 2019: TTS without T
Ewan Dunbar, Robin Algayres, Julien Karadayi +10
We present the Zero Resource Speech Challenge 2019, which proposes to build a speech synthesizer without any text or phonetic labels: hence, TTS without T (text-to-speech without t…
Unsupervised Word Segmentation from Speech with Attention
Pierre Godard, Marcely Zanon-Boito, Lucas Ondel +4
We present a first attempt to perform attentional word segmentation directly from the speech signal, with the final goal to automatically identify lexical units in a low-resource,…
Bayesian Models for Unit Discovery on a Very Low Resource Language
Lucas Ondel, Pierre Godard, Laurent Besacier +7
Developing speech technologies for low-resource languages has become a very active research field over the last decade. Among others, Bayesian models have shown some promising resu…
Linguistic unit discovery from multi-modal inputs in unwritten languages: Summary of the "Speaking Rosetta" JSALT 2017 Workshop
Odette Scharenborg, Laurent Besacier, Alan Black +16
We summarize the accomplishments of a multi-disciplinary workshop exploring the computational and scientific issues surrounding the discovery of linguistic units (subwords and word…
Automatic Speech Recognition and Topic Identification for Almost-Zero-Resource Languages
Matthew Wiesner, Chunxi Liu, Lucas Ondel +6
Automatic speech recognition (ASR) systems often need to be developed for extremely low-resource languages to serve end-uses such as audio content categorization and search. While…