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Edresson Casanova

6 accepted papers

2026

TAGARELA - A PORTUGUESE SPEECH DATASET FROM PODCASTS

Frederico Santos de Oliveira, Lucas Rafael Stefanel Gris, Augusto Seben da Rosa, Alexandre Costa Ferro Filho, Edresson Casanova, Christopher Dane Shulby +2
ICASSP 2026poster

Despite significant advances in speech processing, Portuguese remains under-resourced due to the scarcity of public, large-scale, and high-quality datasets. To address this gap, we present a new dataset, named TAGARELA, composed of over 8,972 hours of podcast audio, specifically curated for training…

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2025

FreeSVC: Towards Zero-shot Multilingual Singing Voice Conversion

Alef Iury Siqueira Ferreira, Lucas Rafael Stefanel Gris, Augusto Seben da Rosa, Frederico Santos de Oliveira, Edresson Casanova, Rafael Teixeira Sousa +3
ICASSP 2025accepted

This work presents FreeSVC, a promising multilingual singing voice conversion approach that leverages an enhanced VITS model with Speaker-invariant Clustering (SPIN) for better content representation and the State-of-the-Art (SOTA) speaker encoder ECAPA2. FreeSVC incorporates trainable language embe…

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2025

Koel-TTS: Enhancing LLM based Speech Generation with Preference Alignment and Classifier Free Guidance

Shehzeen Samarah Hussain, Paarth Neekhara, Xuesong Yang, Edresson Casanova, Subhankar Ghosh, Roy Fejgin +3
EMNLP 2025

Autoregressive speech token generation models produce speech with remarkable variety and naturalness but often suffer from hallucinations and undesired vocalizations that do not conform to conditioning inputs. To address these challenges, we introduce Koel-TTS, an encoder-decoder transformer model f

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2025

Low Frame-rate Speech Codec: a Codec Designed for Fast High-quality Speech LLM Training and Inference

Edresson Casanova, Ryan Langman, Paarth Neekhara, Shehzeen Hussain, Jason Li, Subhankar Ghosh +2
ICASSP 2025accepted

Large language models (LLMs) have significantly advanced audio processing through audio codecs that convert audio into discrete tokens, enabling the application of language modeling techniques to audio data. However, audio codecs often operate at high frame rates, resulting in slow training and infe…

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2025

MuPe Life Stories Dataset: Spontaneous Speech in Brazilian Portuguese with a Case Study Evaluation on ASR Bias against Speakers Groups and Topic Modeling

Sidney Evaldo Leal, Arnaldo Candido Junior, Ricardo Marcacini, Edresson Casanova, Odilon Gonçalves, Anderson Silva Soares +3
COLING 2025main

Recently, several public datasets for automatic speech recognition (ASR) in Brazilian Portuguese (BP) have been released, improving ASR systems performance. However, these datasets lack diversity in terms of age groups, regional accents, and education levels. In this paper, we present a new publicly…

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2022

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

Edresson Casanova, Julian Weber, Christopher D Shulby, Arnaldo Candido Junior, Eren Gölge, Moacir A Ponti
ICML 2022spotlight

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-shot multi-speaker and multilingual training. We achieved state-of-the-art (SOTA) results in zero-shot multi-speaker TTS…

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