activity
20212026
most citedASR data augmentation in low-resource settings using cross-lingual multi-speaker TTS and cross-lingual voice conversion

4 citations · 6 across the 7 of their papers we have counts for

collaborators

9 papers

cs.SD2026

CAL-MOS: Bridging Layers with Adapters for Robust MOS Prediction Across Speech Foundation Models

Alef Iury Siqueira Ferreira, Pedro Lustosa Rege Botelho, Fernanda Silva +5

Speech Quality Assessment (SQA) is essential for modern speech technologies, and recent non-intrusive SQA predictors increasingly rely on Speech Foundation Models (SFMs). However,…

cs.CL2026

CVSS-X: A Multilingual Speech-to-Speech Translation Corpus for 28 Languages

Lucas Rafael Stefanel Gris, Alef Iury Siqueira Ferreira, Frederico Santos de Oliveira +4

We introduce CVSS-X, a large-scale synthetic speech-to-speech translation corpus that extends CVSS by reversing the translation direction. While CVSS translates from 21 languages i…

eess.AS2026

Cloned Voices, Real Consequences: Evaluating Bias in Political Deepfake Detection for Electoral Integrity in Brazil

Lucas Rafael Stefanel Gris, Daniel Casanova, Frederico Santos De Oliveira +4

Recent advances in generative artificial intelligence have made it easier to fabricate statements and amplify political disinformation during elections. We introduce ParlaSpoof-BR,…

cs.SD2026

Mask, Sample, Revise: A Revisable CTMC Inference Stack for Guided Discrete Flow Matching Text-to-Speech

Alef Iury Siqueira Ferreira, Lucas Rafael Stefanel Gris, Luiz Fernando de Araújo Vidal +4

Recent alignment-free non-autoregressive (NAR) text-to-speech (TTS) models formulate synthesis as a conditional infilling task, bypassing explicit duration predictors and external…

cs.CV2023

Yin Yang Convolutional Nets: Image Manifold Extraction by the Analysis of Opposites

Augusto Seben da Rosa, Frederico Santos de Oliveira, Anderson da Silva Soares +1

Computer vision in general presented several advances such as training optimizations, new architectures (pure attention, efficient block, vision language models, generative models,…

eess.AS2023

CML-TTS A Multilingual Dataset for Speech Synthesis in Low-Resource Languages

Frederico S. Oliveira, Edresson Casanova, Arnaldo Cândido Júnior +2

In this paper, we present CML-TTS, a recursive acronym for CML-Multi-Lingual-TTS, a new Text-to-Speech (TTS) dataset developed at the Center of Excellence in Artificial Intelligenc…

cs.SD2023★ 1 cited

Evaluation of Speech Representations for MOS prediction

Frederico S. Oliveira, Edresson Casanova, Arnaldo Cândido Júnior +3

In this paper, we evaluate feature extraction models for predicting speech quality. We also propose a model architecture to compare embeddings of supervised learning and self-super…

eess.AS2022★ 4 cited

ASR data augmentation in low-resource settings using cross-lingual multi-speaker TTS and cross-lingual voice conversion

Edresson Casanova, Christopher Shulby, Alexander Korolev +4

We explore cross-lingual multi-speaker speech synthesis and cross-lingual voice conversion applied to data augmentation for automatic speech recognition (ASR) systems in low/medium…

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…