Roberto Barra-Chicote

Abstract This paper introduces TESSCCo (TV-control EEG-based Silent Speech Command Corpus), a new dataset including electroencephalography (EEG) signals during Overt Speech (OS) and Covert Speech (CS) in different languages. The dataset comprises repetitions of five different commands pronounced covertly and overtly in English and Spanish from 21 healthy native Spanish speakers (13 male, 8 female, 23 ± 2 years old), while EEG and audio were recorded.

In this paper, we propose GlowVC: a multilingual multi-speaker flow-based model for language-independent text-free voice conversion. We build on Glow-TTS, which provides an architecture that enables use of linguistic features during training without the necessity of using them for VC inference. We consider two versions of our model: GlowVC-conditional and GlowVC-explicit.

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