Driss Matrouf


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RoboVox: A Single/Multi-channel Far-field Speaker Recognition Benchmark for a Mobile Robot
Mohammad Mohammadamini | Driss Matrouf | Michael Rouvier | Jean-Francois Bonastre | Romain Serizel | Theophile Gonos
Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)

In this paper, we introduce a new far-field speaker recognition benchmark called RoboVox. RoboVox is a French corpus recorded by a mobile robot. The files are recorded from different distances under severe acoustical conditions with the presence of several types of noise and reverberation. In addition to noise and reverberation, the robot’s internal noise acts as an extra additive noise. RoboVox can be used for both single-channel and multi-channel speaker recognition. In the evaluation protocols, we are considering both cases. The obtained results demonstrate a significant decline in performance in far-filed speaker recognition and urge the community to further research in this domain


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An I-vector Based Approach to Compact Multi-Granularity Topic Spaces Representation of Textual Documents
Mohamed Morchid | Mohamed Bouallegue | Richard Dufour | Georges Linarès | Driss Matrouf | Renato de Mori
Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)


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Analyse en Composante Principale pour l’extraction des i-vecteurs en vérification du locuteur (Principal Component Analysis for i-vector extraction in speaker verification.) [in French]
Anthony Larcher | Pierre-Michel Bousquet | Driss Matrouf | Jean-Francois Bonastre
Proceedings of the Joint Conference JEP-TALN-RECITAL 2012, volume 1: JEP