activity
20202025
most citedYourTTS: Towards Zero-Shot Multi-Speaker TTS and Zero-Shot Voice Conversion for everyone

32 citations · 66 across the 9 of their papers we have counts for

collaborators

11 papers

cs.CL2025

The Impact of Prosodic Segmentation on Speech Synthesis of Spontaneous Speech

Julio Cesar Galdino, Sidney Evaldo Leal, Leticia Gabriella De Souza +6

Spontaneous speech presents several challenges for speech synthesis, particularly in capturing the natural flow of conversation, including turn-taking, pauses, and disfluencies. Al…

eess.AS2024

XTTS: a Massively Multilingual Zero-Shot Text-to-Speech Model

Edresson Casanova, Kelly Davis, Eren Gölge +8

Most Zero-shot Multi-speaker TTS (ZS-TTS) systems support only a single language. Although models like YourTTS, VALL-E X, Mega-TTS 2, and Voicebox explored Multilingual ZS-TTS they…

cs.SD2024★ 5 cited

MLAAD: The Multi-Language Audio Anti-Spoofing Dataset

Nicolas M. Müller, Piotr Kawa, Wei Herng Choong +6

This paper presents the Multi-Language Audio Anti-Spoofing Dataset (MLAAD), version 11: a dataset of synthetic audio to train and evaluate audio deepfake detection models. It featu…

eess.AS2022

Interpretability Analysis of Deep Models for COVID-19 Detection

Daniel Peixoto Pinto da Silva, Edresson Casanova, Lucas Rafael Stefanel Gris +8

During the outbreak of COVID-19 pandemic, several research areas joined efforts to mitigate the damages caused by SARS-CoV-2. In this paper we present an interpretability analysis…

cs.SD2021★ 32 cited

YourTTS: Towards Zero-Shot Multi-Speaker TTS and Zero-Shot Voice Conversion for everyone

Edresson Casanova, Julian Weber, Christopher Shulby +3

YourTTS brings the power of a multilingual approach to the task of zero-shot multi-speaker TTS. Our method builds upon the VITS model and adds several novel modifications for zero-…

cs.CL2021★ 10 cited

CORAA: a large corpus of spontaneous and prepared speech manually validated for speech recognition in Brazilian Portuguese

Arnaldo Candido Junior, Edresson Casanova, Anderson Soares +8

Automatic Speech recognition (ASR) is a complex and challenging task. In recent years, there have been significant advances in the area. In particular, for the Brazilian Portuguese…

physics.med-ph2021★ 2 cited

Performance evaluation in the reconstruction of 2D images of computed tomography using massively parallel programming CUDA

Alexssandro Ferreira Cordeiro, Pedro Luiz de Paula Filho, Hamilton Pereira da Silva +3

Analysis of processing time and similarity of images generated between CPU and GPU architectures and sequential and parallel programming. For image processing a computer with AMD F…

cs.CL2021★ 1 cited

Brazilian Portuguese Speech Recognition Using Wav2vec 2.0

Lucas Rafael Stefanel Gris, Edresson Casanova, Frederico Santos de Oliveira +2

Deep learning techniques have been shown to be efficient in various tasks, especially in the development of speech recognition systems, that is, systems that aim to transcribe an a…

eess.AS2021

SC-GlowTTS: an Efficient Zero-Shot Multi-Speaker Text-To-Speech Model

Edresson Casanova, Christopher Shulby, Eren Gölge +6

In this paper, we propose SC-GlowTTS: an efficient zero-shot multi-speaker text-to-speech model that improves similarity for speakers unseen during training. We propose a speaker-c…

eess.AS2020★ 16 cited

TTS-Portuguese Corpus: a corpus for speech synthesis in Brazilian Portuguese

Edresson Casanova, Arnaldo Candido Junior, Christopher Shulby +4

Speech provides a natural way for human-computer interaction. In particular, speech synthesis systems are popular in different applications, such as personal assistants, GPS applic…

cs.CL2020

Speech2Phone: A Novel and Efficient Method for Training Speaker Recognition Models

Edresson Casanova, Arnaldo Candido Junior, Christopher Shulby +5

In this paper we present an efficient method for training models for speaker recognition using small or under-resourced datasets. This method requires less data than other SOTA (St…