7 citations · 10 across the 10 of their papers we have counts for
5 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…
Investigating Content-Aware Neural Text-To-Speech MOS Prediction Using Prosodic and Linguistic Features
Alexandra Vioni, Georgia Maniati, Nikolaos Ellinas +4
Current state-of-the-art methods for automatic synthetic speech evaluation are based on MOS prediction neural models. Such MOS prediction models include MOSNet and LDNet that use s…
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…