Search Results for author: Kamil Pokora

Found 8 papers, 0 papers with code

Enhancing audio quality for expressive Neural Text-to-Speech

no code implementations13 Aug 2021 Abdelhamid Ezzerg, Adam Gabrys, Bartosz Putrycz, Daniel Korzekwa, Daniel Saez-Trigueros, David McHardy, Kamil Pokora, Jakub Lachowicz, Jaime Lorenzo-Trueba, Viacheslav Klimkov

Artificial speech synthesis has made a great leap in terms of naturalness as recent Text-to-Speech (TTS) systems are capable of producing speech with similar quality to human recordings.

Acoustic Modelling Speech Synthesis

Remap, warp and attend: Non-parallel many-to-many accent conversion with Normalizing Flows

no code implementations10 Nov 2022 Abdelhamid Ezzerg, Thomas Merritt, Kayoko Yanagisawa, Piotr Bilinski, Magdalena Proszewska, Kamil Pokora, Renard Korzeniowski, Roberto Barra-Chicote, Daniel Korzekwa

Regional accents of the same language affect not only how words are pronounced (i. e., phonetic content), but also impact prosodic aspects of speech such as speaking rate and intonation.

On granularity of prosodic representations in expressive text-to-speech

no code implementations26 Jan 2023 Mikolaj Babianski, Kamil Pokora, Raahil Shah, Rafal Sienkiewicz, Daniel Korzekwa, Viacheslav Klimkov

In expressive speech synthesis it is widely adopted to use latent prosody representations to deal with variability of the data during training.

Expressive Speech Synthesis

Creating New Voices using Normalizing Flows

no code implementations22 Dec 2023 Piotr Bilinski, Thomas Merritt, Abdelhamid Ezzerg, Kamil Pokora, Sebastian Cygert, Kayoko Yanagisawa, Roberto Barra-Chicote, Daniel Korzekwa

As there is growing interest in synthesizing voices of new speakers, here we investigate the ability of normalizing flows in text-to-speech (TTS) and voice conversion (VC) modes to extrapolate from speakers observed during training to create unseen speaker identities.

Speech Synthesis Voice Conversion

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