Search Results for author: Abdelhamid Ezzerg

Found 5 papers, 0 papers with code

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.

GlowVC: Mel-spectrogram space disentangling model for language-independent text-free voice conversion

no code implementations4 Jul 2022 Magdalena Proszewska, Grzegorz Beringer, Daniel Sáez-Trigueros, Thomas Merritt, Abdelhamid Ezzerg, Roberto Barra-Chicote

We evaluate our models in terms of intelligibility, speaker similarity and naturalness for intra- and cross-lingual conversion in seen and unseen languages.

Voice Conversion

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

Non-Autoregressive TTS with Explicit Duration Modelling for Low-Resource Highly Expressive Speech

no code implementations24 Jun 2021 Raahil Shah, Kamil Pokora, Abdelhamid Ezzerg, Viacheslav Klimkov, Goeric Huybrechts, Bartosz Putrycz, Daniel Korzekwa, Thomas Merritt

In this paper, we present a method for building highly expressive TTS voices with as little as 15 minutes of speech data from the target speaker.

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