  Speech resynthesis is a generic task for which we want to synthesize audio
with another audio as input, which finds applications for media monitors and
journalists.Among different tasks addressed by speech resynthesis, voice
conversion preserves the linguistic information while modifying the identity of
the speaker, and speech edition preserves the identity of the speaker but some
words are modified.In both cases, we need to disentangle speaker and phonetic
contents in intermediate representations.Phonetic PosteriorGrams (PPG) are a
frame-level probabilistic representation of phonemes, and are usually
considered speaker-independent.This paper presents a PPG-based speech
resynthesis system.A perceptive evaluation assesses that it produces correct
audio quality.Then, we demonstrate that an automatic speaker verification model
is not able to recover the source speaker after re-synthesis with PPG, even
when the model is trained on synthetic data.
