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

27 citations · 121 across the 16 of their papers we have counts for

collaborators

16 papers

cs.SD2022★ 6 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…

cs.SD2022★ 1 cited

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…

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…

eess.AS2022

Bunched LPCNet2: Efficient Neural Vocoders Covering Devices from Cloud to Edge

Sangjun Park, Kihyun Choo, Joohyung Lee +3

Text-to-Speech (TTS) services that run on edge devices have many advantages compared to cloud TTS, e.g., latency and privacy issues. However, neural vocoders with a low complexity…

cs.SD2021★ 6 cited

Prosodic Clustering for Phoneme-level Prosody Control in End-to-End Speech Synthesis

Alexandra Vioni, Myrsini Christidou, Nikolaos Ellinas +7

This paper presents a method for controlling the prosody at the phoneme level in an autoregressive attention-based text-to-speech system. Instead of learning latent prosodic featur…

cs.SD2021★ 5 cited

Word-Level Style Control for Expressive, Non-attentive Speech Synthesis

Konstantinos Klapsas, Nikolaos Ellinas, June Sig Sung +2

This paper presents an expressive speech synthesis architecture for modeling and controlling the speaking style at a word level. It attempts to learn word-level stylistic and proso…

cs.SD2021★ 2 cited

Improved Prosodic Clustering for Multispeaker and Speaker-independent Phoneme-level Prosody Control

Myrsini Christidou, Alexandra Vioni, Nikolaos Ellinas +7

This paper presents a method for phoneme-level prosody control of F0 and duration on a multispeaker text-to-speech setup, which is based on prosodic clustering. An autoregressive a…

cs.SD2021★ 2 cited

Rapping-Singing Voice Synthesis based on Phoneme-level Prosody Control

Konstantinos Markopoulos, Nikolaos Ellinas, Alexandra Vioni +8

In this paper, a text-to-rapping/singing system is introduced, which can be adapted to any speaker's voice. It utilizes a Tacotron-based multispeaker acoustic model trained on read…

cs.SD2021★ 13 cited

Cross-lingual Low Resource Speaker Adaptation Using Phonological Features

Georgia Maniati, Nikolaos Ellinas, Konstantinos Markopoulos +5

The idea of using phonological features instead of phonemes as input to sequence-to-sequence TTS has been recently proposed for zero-shot multilingual speech synthesis. This approa…

cs.SD2021★ 25 cited

High Quality Streaming Speech Synthesis with Low, Sentence-Length-Independent Latency

Nikolaos Ellinas, Georgios Vamvoukakis, Konstantinos Markopoulos +7

This paper presents an end-to-end text-to-speech system with low latency on a CPU, suitable for real-time applications. The system is composed of an autoregressive attention-based…

eess.AS2021★ 26 cited

Expressive Text-to-Speech using Style Tag

Minchan Kim, Sung Jun Cheon, Byoung Jin Choi +2

As recent text-to-speech (TTS) systems have been rapidly improved in speech quality and generation speed, many researchers now focus on a more challenging issue: expressive TTS. To…