27 citations · 37 across the 11 of their papers we have counts for
9 papers · 1 filter
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…
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…
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…
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…
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…
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…
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…
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…