  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.
