Search Results for author: Mirko Bronzi

Found 4 papers, 2 papers with code

On Using Transformers for Speech-Separation

1 code implementation6 Feb 2022 Cem Subakan, Mirco Ravanelli, Samuele Cornell, Francois Grondin, Mirko Bronzi

In this paper, we extend our previous work by providing results on more datasets including LibriMix, and WHAM!, WHAMR!

Denoising Speech Enhancement +1

Accounting for Variance in Machine Learning Benchmarks

no code implementations1 Mar 2021 Xavier Bouthillier, Pierre Delaunay, Mirko Bronzi, Assya Trofimov, Brennan Nichyporuk, Justin Szeto, Naz Sepah, Edward Raff, Kanika Madan, Vikram Voleti, Samira Ebrahimi Kahou, Vincent Michalski, Dmitriy Serdyuk, Tal Arbel, Chris Pal, Gaël Varoquaux, Pascal Vincent

Strong empirical evidence that one machine-learning algorithm A outperforms another one B ideally calls for multiple trials optimizing the learning pipeline over sources of variation such as data sampling, data augmentation, parameter initialization, and hyperparameters choices.

Data Augmentation

Attention is All You Need in Speech Separation

3 code implementations25 Oct 2020 Cem Subakan, Mirco Ravanelli, Samuele Cornell, Mirko Bronzi, Jianyuan Zhong

Transformers are emerging as a natural alternative to standard RNNs, replacing recurrent computations with a multi-head attention mechanism.

Speech Separation

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