activity
20222025
most citedSOMOS: The Samsung Open MOS Dataset for the Evaluation of Neural Text-to-Speech Synthesis

27 citations · 37 across the 11 of their papers we have counts for

collaborators

11 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.SD2025

Counterfactual Activation Editing for Post-hoc Prosody and Mispronunciation Correction in TTS Models

Kyowoon Lee, Artyom Stitsyuk, Gunu Jho +2

Recent advances in Text-to-Speech (TTS) have significantly improved speech naturalness, increasing the demand for precise prosody control and mispronunciation correction. Existing…

cs.SD2024

Investigating Disentanglement in a Phoneme-level Speech Codec for Prosody Modeling

Sotirios Karapiperis, Nikolaos Ellinas, Alexandra Vioni +4

Most of the prevalent approaches in speech prosody modeling rely on learning global style representations in a continuous latent space which encode and transfer the attributes of r…

cs.LG2024★ 2 cited

Improved Text Emotion Prediction Using Combined Valence and Arousal Ordinal Classification

Michael Mitsios, Georgios Vamvoukakis, Georgia Maniati +13

Emotion detection in textual data has received growing interest in recent years, as it is pivotal for developing empathetic human-computer interaction systems. This paper introduce…

cs.SD2024

Low-Resource Cross-Domain Singing Voice Synthesis via Reduced Self-Supervised Speech Representations

Panos Kakoulidis, Nikolaos Ellinas, Georgios Vamvoukakis +8

In this paper, we propose a singing voice synthesis model, Karaoker-SSL, that is trained only on text and speech data as a typical multi-speaker acoustic model. It is a low-resourc…

cs.SD2022

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…

cs.SD2022★ 5 cited

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…

eess.AS2022★ 3 cited

Karaoker: Alignment-free singing voice synthesis with speech training data

Panos Kakoulidis, Nikolaos Ellinas, Georgios Vamvoukakis +5

Existing singing voice synthesis models (SVS) are usually trained on singing data and depend on either error-prone time-alignment and duration features or explicit music score info…

cs.SD2022

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…

cs.SD2022★ 27 cited

SOMOS: The Samsung Open MOS Dataset for the Evaluation of Neural Text-to-Speech Synthesis

Georgia Maniati, Alexandra Vioni, Nikolaos Ellinas +6

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…