25 citations · 38 across the 10 of their papers we have counts for
6 papers · 1 filter
Predicting phoneme-level prosody latents using AR and flow-based Prior Networks for expressive speech synthesis
Konstantinos Klapsas, Karolos Nikitaras, Nikolaos Ellinas +5
A large part of the expressive speech synthesis literature focuses on learning prosodic representations of the speech signal which are then modeled by a prior distribution during i…
Learning utterance-level representations through token-level acoustic latents prediction for Expressive Speech Synthesis
Karolos Nikitaras, Konstantinos Klapsas, Nikolaos Ellinas +6
This paper proposes an Expressive Speech Synthesis model that utilizes token-level latent prosodic variables in order to capture and control utterance-level attributes, such as cha…
Generating Multilingual Gender-Ambiguous Text-to-Speech Voices
Konstantinos Markopoulos, Georgia Maniati, Georgios Vamvoukakis +9
The gender of any voice user interface is a key element of its perceived identity. Recently, there has been increasing interest in interfaces where the gender is ambiguous rather t…
Cross-lingual Text-To-Speech with Flow-based Voice Conversion for Improved Pronunciation
Nikolaos Ellinas, Georgios Vamvoukakis, Konstantinos Markopoulos +7
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 langu…
Fine-grained Noise Control for Multispeaker Speech Synthesis
Karolos Nikitaras, Georgios Vamvoukakis, Nikolaos Ellinas +7
A text-to-speech (TTS) model typically factorizes speech attributes such as content, speaker and prosody into disentangled representations.Recent works aim to additionally model th…
Self-supervised learning for robust voice cloning
Konstantinos Klapsas, Nikolaos Ellinas, Karolos Nikitaras +8
Voice cloning is a difficult task which requires robust and informative features incorporated in a high quality TTS system in order to effectively copy an unseen speaker's voice. I…