Feb. 28, 2024, 5:43 a.m. | Nikolaos Ellinas, Georgios Vamvoukakis, Konstantinos Markopoulos, Georgia Maniati, Panos Kakoulidis, June Sig Sung, Inchul Hwang, Spyros Raptis, Aimil

cs.LG updates on arXiv.org arxiv.org

arXiv:2210.17264v2 Announce Type: replace-cross
Abstract: This paper presents a method for end-to-end cross-lingual text-to-speech (TTS) which aims to preserve the target language's pronunciation regardless of the original speaker's language. The model used is based on a non-attentive Tacotron architecture, where the decoder has been replaced with a normalizing flow network conditioned on the speaker identity, allowing both TTS and voice conversion (VC) to be performed by the same model due to the inherent linguistic content and speaker identity disentanglement. When …

abstract architecture arxiv conversion cross-lingual cs.cl cs.lg cs.sd decoder eess.as flow language network paper speaker speech text text-to-speech the decoder tts type voice

Founding AI Engineer, Agents

@ Occam AI | New York

AI Engineer Intern, Agents

@ Occam AI | US

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne