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The Zero Resource Speech Challenge 2019: TTS without T

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arxiv 1904.11469 v2 pith:I4WYKL7L submitted 2019-04-25 cs.CL cs.SDeess.AS

Ewan Dunbar , Robin Algayres , Julien Karadayi , Mathieu Bernard , Juan Benjumea , Xuan-Nga Cao , Lucie Miskic , Charlotte Dugrain
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Lucas Ondel Alan W. Black Laurent Besacier Sakriani Sakti Emmanuel Dupoux
This is my paper
classification cs.CLcs.SDeess.AS
keywords voicewithoutspeechtextchallengedatasetdiscoverylabels
verification ladder T0 review T1 audit T2 compute T3 formal
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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 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 topline TTS using gold phoneme transcriptions. We present an overview of the 19 submitted systems from 10 teams and discuss the main results.

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