Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Putrycz, Bartosz"'
Autor:
Łajszczak, Mateusz, Cámbara, Guillermo, Li, Yang, Beyhan, Fatih, van Korlaar, Arent, Yang, Fan, Joly, Arnaud, Martín-Cortinas, Álvaro, Abbas, Ammar, Michalski, Adam, Moinet, Alexis, Karlapati, Sri, Muszyńska, Ewa, Guo, Haohan, Putrycz, Bartosz, Gambino, Soledad López, Yoo, Kayeon, Sokolova, Elena, Drugman, Thomas
We introduce a text-to-speech (TTS) model called BASE TTS, which stands for $\textbf{B}$ig $\textbf{A}$daptive $\textbf{S}$treamable TTS with $\textbf{E}$mergent abilities. BASE TTS is the largest TTS model to-date, trained on 100K hours of public do
Externí odkaz:
http://arxiv.org/abs/2402.08093
Autor:
Ezzerg, Abdelhamid, Gabrys, Adam, Putrycz, Bartosz, Korzekwa, Daniel, Saez-Trigueros, Daniel, McHardy, David, Pokora, Kamil, Lachowicz, Jakub, Lorenzo-Trueba, Jaime, Klimkov, Viacheslav
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. However, not all speaking styles are easy to model: highly expr
Externí odkaz:
http://arxiv.org/abs/2108.06270
Autor:
Shah, Raahil, Pokora, Kamil, Ezzerg, Abdelhamid, Klimkov, Viacheslav, Huybrechts, Goeric, Putrycz, Bartosz, Korzekwa, Daniel, Merritt, Thomas
Whilst recent neural text-to-speech (TTS) approaches produce high-quality speech, they typically require a large amount of recordings from the target speaker. In previous work, a 3-step method was proposed to generate high-quality TTS while greatly r
Externí odkaz:
http://arxiv.org/abs/2106.12896
Autor:
Jiao, Yunlong, Gabrys, Adam, Tinchev, Georgi, Putrycz, Bartosz, Korzekwa, Daniel, Klimkov, Viacheslav
We present a universal neural vocoder based on Parallel WaveNet, with an additional conditioning network called Audio Encoder. Our universal vocoder offers real-time high-quality speech synthesis on a wide range of use cases. We tested it on 43 inter
Externí odkaz:
http://arxiv.org/abs/2102.01106
Autor:
Merritt, Thomas, Putrycz, Bartosz, Nadolski, Adam, Ye, Tianjun, Korzekwa, Daniel, Dolecki, Wiktor, Drugman, Thomas, Klimkov, Viacheslav, Moinet, Alexis, Breen, Andrew, Kuklinski, Rafal, Strom, Nikko, Barra-Chicote, Roberto
Statistical TTS systems that directly predict the speech waveform have recently reported improvements in synthesis quality. This investigation evaluates Amazon's statistical speech waveform synthesis (SSWS) system. An in-depth evaluation of SSWS is c
Externí odkaz:
http://arxiv.org/abs/1811.06296
Autor:
Lorenzo-Trueba, Jaime, Drugman, Thomas, Latorre, Javier, Merritt, Thomas, Putrycz, Bartosz, Barra-Chicote, Roberto, Moinet, Alexis, Aggarwal, Vatsal
This paper explores the potential universality of neural vocoders. We train a WaveRNN-based vocoder on 74 speakers coming from 17 languages. This vocoder is shown to be capable of generating speech of consistently good quality (98% relative mean MUSH
Externí odkaz:
http://arxiv.org/abs/1811.06292
Autor:
Lutowski, Rafał, Putrycz, Bartosz
We present an algorithmic approach to the problem of existence of spin structures on flat manifolds. We apply our method in the cases of flat manifolds of dimensions 5 and 6.
Externí odkaz:
http://arxiv.org/abs/1411.7799
Autor:
Petrosyan, Nansen, Putrycz, Bartosz
We disprove a conjecture stating that the integral cohomology of any crystallographic group Z^n \rtimes Z_m is given by the cohomology of Z_m with coefficients in the cohomology of the group Z^n, by providing a complete list of counterexamples up to
Externí odkaz:
http://arxiv.org/abs/1106.4216
Autor:
Lutowski, Rafał, Putrycz, Bartosz
Publikováno v:
In Journal of Algebra 15 August 2015 436:277-291
Autor:
Petrosyan, Nansen, Putrycz, Bartosz
Publikováno v:
In Journal of Algebra 1 October 2012 367:237-246