Topic: In this Master thesis, we address the problem of speech separation given single-channel microphone mixed speech and video frames of the involved speakers. Although there exist several audio-only speech separation methods [1], here, we aim to utilize also the visual information, that is, video frames of speakers’ lips. This…
Topic: In this Master thesis we address the problem of how to robustly train a ConvNet for regression, or deep robust regression [1,2]. Traditionally, deep regression employs the L2 loss function [3], known to be sensitive to outliers, i.e. samples that either lie at an abnormal distance away from the…
Starting Date: February 1st, 2020. Funding: The H2020 ICT SPRING Project Contact Point: Xavier Alameda-Pineda Duration: From 2 and up to 4 years. To apply: https://jobs.inria.fr/public/classic/fr/offres/2019-02083 General Context: SPRING – Socially Pertinent Robots in Gerontological Healthcare – is a 4-year R&D project fully funded by the European Comission under the H2020…
Starting Date:November 1st, 2019 – February 1st, 2020. Funding: The H2020 ICT SPRING Project Contact Point: Xavier Alameda-Pineda Duration: 2 years and up to 4 years. To apply: https://jobs.inria.fr/public/classic/fr/offres/2019-02081 General Context: SPRING – Socially Pertinent Robots in Gerontological Healthcare – is a 4-year R&D project fully funded by the European Comission…
Starting Date: November 1st, 2019 – February 1st, 2020. Duration: 2 years and up to 4 years. Funding: The H2020 ICT SPRING Project Contact Point: Xavier Alameda-Pineda To apply: https://jobs.inria.fr/public/classic/fr/offres/2019-02082 General Context: SPRING – Socially Pertinent Robots in Gerontological Healthcare – is a 4-year R&D project fully funded by the European…
The Perception team is happy to announce that a new project has been awarded by the European Union under the H2020-ICT program. The main objective of SPRING (Socially Pertinent Robots in Gerontological Healthcare) is the development of socially assistive robots with the capacity of performing multimodal multiple-person interaction and open-domain dialogue….
MSc. Project on Speaker identity modeling with deep learning for re-identification Short description: Speaker identification is the task that aims at determining which speaker has produced a given utterance [1]. On the other hand, speaker verification or re-identification aims at determining whether there is a match between a given speech…
MSc. Project on Coupled Audio-visual Multi-speaker Tracking Short description: Multi-speaker tracking has been widely investigated and the Perception team contributed with a consistent methodological framework based on variational Bayes techniques [1-4]. Often, audio-visual tracking methods first map all auditory and visual information in the same space, to later on run…
MSc project on “Gazeable Objects” Duration: about 6 months Short description: Gaze is the direction towards which a person is looking. The automatic estimation of the gaze from a single image and from videos has been a hot research topic in previous years [1-4]. Often, researchers studied gaze from a human-centered…
Multi-Microphone Speaker Localization on Manifolds: Achievements and Challenges Wednesday, September 27th 2017, 10:30 – 12:00, room F107, INRIA Montbonnot Seminar by Prof. Sharon Gannot, Bar-Ilan University, Israel joint work with Bracha Laufer-Goldshtein, Bar-Ilan University, Israel and Prof. Ronen Talmon, The Technion-IIT, Israel Abstract: Speech enhancement is a core problem in audio…
