most citedControllable speech synthesis by learning discrete phoneme-level prosodic representations

6 citations · 6 across the 4 of their papers we have counts for

collaborators

5 papers

cs.SD2025

Pseudo-Cepstrum: Pitch Modification for Mel-Based Neural Vocoders

Nikolaos Ellinas, Alexandra Vioni, Panos Kakoulidis +8

This paper introduces a cepstrum-based pitch modification method that can be applied to any mel-spectrogram representation. As a result, this method is compatible with any mel-base…

cs.SD2025

MambaRate: Speech Quality Assessment Across Different Sampling Rates

Panos Kakoulidis, Iakovi Alexiou, Junkwang Oh +4

We propose MambaRate, which predicts Mean Opinion Scores (MOS) with limited bias regarding the sampling rate of the waveform under evaluation. It is designed for Track 3 of the Aud…

cs.SD20226 cited

Controllable speech synthesis by learning discrete phoneme-level prosodic representations

Nikolaos Ellinas, Myrsini Christidou, Alexandra Vioni +4

In this paper, we present a novel method for phoneme-level prosody control of F0 and duration using intuitive discrete labels. We propose an unsupervised prosodic clustering proces…

cs.SD2022

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…

cs.SD2022

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…