Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Georgia Maniati"'
Autor:
Georgia Maniati, Alexandra Vioni, Nikolaos Ellinas, Karolos Nikitaras, Konstantinos Klapsas, June Sig Sung, Gunu Jho, Aimilios Chalamandaris, Pirros Tsiakoulis
In this work, we present the SOMOS dataset, the first large-scale mean opinion scores (MOS) dataset consisting of solely neural text-to-speech (TTS) samples. It can be employed to train automatic MOS prediction systems focused on the assessment of mo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cc651faeaa04115356a3dc709682b63a
http://arxiv.org/abs/2204.03040
http://arxiv.org/abs/2204.03040
Autor:
Aimilios Chalamandaris, Georgios Vamvoukakis, Nikolaos Ellinas, Konstantinos Markopoulos, Pirros Tsiakoulis, June Sig Sung, Hyoungmin Park, Georgia Maniati
The idea of using phonological features instead of phonemes as input to sequence-to-sequence TTS has been recently proposed for zero-shot multilingual speech synthesis. This approach is useful for code-switching, as it facilitates the seamless utteri
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1a24fc2c09faa4d72db9308dddd537a4
http://arxiv.org/abs/2111.09075
http://arxiv.org/abs/2111.09075
Autor:
Konstantinos Markopoulos, Myrsini Christidou, June Sig Sung, Aimilios Chalamandaris, Pirros Tsiakoulis, Georgios Vamvoukakis, Alexandra Vioni, Panos Kakoulidis, Hyoungmin Park, Nikolaos Ellinas, Georgia Maniati
In this paper, a text-to-rapping/singing system is introduced, which can be adapted to any speaker's voice. It utilizes a Tacotron-based multispeaker acoustic model trained on read-only speech data and which provides prosody control at the phoneme le
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::16fb08b35ac399ca9b1c19767b2451d6
http://arxiv.org/abs/2111.09146
http://arxiv.org/abs/2111.09146
Autor:
June Sig Sung, Spyros Raptis, Pirros Tsiakoulis, Nikolaos Ellinas, Aimilios Chalamandaris, Hyoungmin Park, Georgia Maniati, Georgios Vamvoukakis, Panos Kakoulidis, Konstantinos Markopoulos
Publikováno v:
INTERSPEECH
This paper presents an end-to-end text-to-speech system with low latency on a CPU, suitable for real-time applications. The system is composed of an autoregressive attention-based sequence-to-sequence acoustic model and the LPCNet vocoder for wavefor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::13c056ca9a78a01703950c53571922b5
https://doi.org/10.21437/interspeech.2020-2464
https://doi.org/10.21437/interspeech.2020-2464
