Portrait of Mirco Ravanelli

Mirco Ravanelli

Associate Academic Member
Associate Professor, Concordia University
Adjunct Professor, Université de Montréal, Department of Computer Science and Operations Research
Research Topics
Deep Learning

Biography

I am an AI researcher, educator, and open-source leader working on the next generation of intelligent machines. I am also an Associate Professor at Concordia University, Adjunct Professor at Université de Montréal, and Associate Member of Mila – Quebec AI Institute. My research focuses on deep learning for Conversational AI, multimodal foundation models, interpretable AI, and efficient machine learning.

My work has resulted in over 100 scientific publications and has been recognized through international awards, including the Amazon Research Award. I had the privilege of completing my postdoctoral training at Mila under the supervision of Yoshua Bengio.

I am the founder and leader of SpeechBrain, one of the world's most widely adopted open-source toolkits for speech and conversational AI, used by researchers and engineers across academia and industry. SpeechBrain has become a global community effort, helping democratize access to cutting-edge AI technologies.

Beyond research, I am passionate about education and mentorship. I believe that advancing AI requires not only scientific breakthroughs but also training the next generation of researchers and engineers to develop AI responsibly and for the benefit of society.

Research interests: Conversational AI • Multimodal LLMs • Audio Tokens • Representation Learning • Interpretable AI • Efficient Deep Learning • Open-Source AI

Current Students

Undergraduate - Concordia University
Research Intern - Concordia University
Master's Research - Concordia University University
Master's Research - Concordia University
Collaborating researcher
Principal supervisor :
Master's Research - Concordia University
PhD - Concordia University
Co-supervisor :
Master's Research - Concordia University
Co-supervisor :
Master's Research - Concordia University
Master's Research - Concordia University University
Research Intern - Concordia University
Collaborating researcher - Université Laval
Principal supervisor :
PhD - Université Laval
Principal supervisor :
Professional Master's - Concordia University Univesity
Collaborating Alumni - Université de Montréal
Principal supervisor :
Postdoctorate - McGill University
PhD - Université de Montréal
Research Intern - Concordia University

Publications

Speaker Recognition from Raw Waveform with SincNet
Deep learning is progressively gaining popularity as a viable alternative to i-vectors for speaker recognition. Promising results have been … (see more)recently obtained with Convolutional Neural Networks (CNNs) when fed by raw speech samples directly. Rather than employing standard hand-crafted features, the latter CNNs learn low-level speech representations from waveforms, potentially allowing the network to better capture important narrow-band speaker characteristics such as pitch and formants. Proper design of the neural network is crucial to achieve this goal. This paper proposes a novel CNN architecture, called SincNet, that encourages the first convolutional layer to discover more meaningful filters. SincNet is based on parametrized sinc functions, which implement band-pass filters. In contrast to standard CNNs, that learn all elements of each filter, only low and high cutoff frequencies are directly learned from data with the proposed method. This offers a very compact and efficient way to derive a customized filter bank specifically tuned for the desired application. Our experiments, conducted on both speaker identification and speaker verification tasks, show that the proposed architecture converges faster and performs better than a standard CNN on raw waveforms.