3 citations · 3 across the 5 of their papers we have counts for
5 papers
Synthetic speech detection in Brazilian Portuguese through accent-related features
Pedro H. L. Leite, Pedro Benevenuto Valadares, Luiz Wagner Pereira Biscainho
Leading commercial and open-source Text-to-Speech (TTS) models fail to emulate the regional phonetic diversity of Brazilian Portuguese (pt-BR). By aggregating disparate dialects in…
Extracting accent features in spoken Brazilian Portuguese without sociolinguistic labels
Pedro H. L. Leite, Pedro Benevenuto Valadares, Luiz W. P. Biscainho
Regional accent classification in Brazilian Portuguese (pt-BR) suffers from the need for reliable labeling. While large self-supervised learning (SSL) speech models are powerful, t…
Complex-Valued Neural Networks for Ultra-Reliable Massive MIMO
Pedro Benevenuto Valadares, Jonathan Aguiar Soares, Kayol Mayer +1
In the evolving landscape of 5G and 6G networks, the demands extend beyond high data rates, ultra-low latency, and extensive coverage, increasingly emphasizing the need for reliabi…
PCA-based Channel Estimation for MIMO Communications
Jonathan Aguiar Soares, Kayol Soares Mayer, Pedro Benevenuto Valadares +1
In multiple-input multiple-output communications, channel estimation is paramount to keep base stations and users on track. This paper proposes a novel PCA-based-principal componen…
Song Emotion Recognition: a Performance Comparison Between Audio Features and Artificial Neural Networks
Karen Rosero, Arthur Nicholas dos Santos, Pedro Benevenuto Valadares +1
When songs are composed or performed, there is often an intent by the singer/songwriter of expressing feelings or emotions through it. For humans, matching the emotiveness in a mus…