Hello! I am a third-year PhD student at Telecom Paris, working on machine learning for audio and music processing under the supervision of prof. Gaël Richard and prof. Geoffroy Peeters. I am part of the ADASP group and the HI-Audio project. I am currently working as a research scientist intern at Deezer research. Previously, I was an intern at Sony CSL (Music Team).
My research focuses on developing novel approaches at the intersection of signal processing and deep learning for Music Information Retrieval (MIR), Music Source Separation and audio synthesis. I am particularly interested in unsupervised and self-supervised learning for training smart and efficient models.
I hold a Bachelor's in Electrical and Computer Engineering from Universidade Federal de Minas Gerais and an engineering degree from Telecom Paris. In 2022, I completed my Master's degree in Artificial Intelligence from the MVA program at Ecole Normale Superieure Paris-Saclay.
Contact: bernardo [dot] torres AT telecom-paris [dot] fr
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You can find my CV here.
PESTO: Real-Time Pitch Estimation with Self-supervised Transposition-equivariant Objective
Alain Riou, Bernardo Torres, Ben Hayes, Stefan Lattner, Gaëtan Hadjeres, Gaël Richard, Geoffroy Peeters
Submitted to Transactions of the International Society of Music Information Retrieval (TISMIR).
ABS
Preprint (soon)
code
Unsupervised Harmonic Parameter Estimation Using Differentiable DSP and Spectral Optimal Transport
Bernardo Torres, Geoffroy Peeters and Gaël Richard
In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2024).
ABS
PDF (arXiv)
code
poster