[Closed] Master internship on Switching Variational Autoencoders for Audio-visual Speech Separation

Context: Over the past years, variational autoencoders (VAEs) have proven efficient for generative modeling of complicated signals, e.g. speech and audio [1]. Recently, they have successfully been applied to audio-visual speech separation (AVSS) [2], where the goal is to separate a target speech from a mixture of several speech signals,…

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[Closed] Master Internship on Meta and Transfer Learning for Deep Reinforcement Learning in Robotics

Topic: The internship is part of our research project into Deep Reinforcement Learning (DRL) [1] for the European SPRING project. SPRING aims to develop control mechanisms for mobile robots that will be employed in hospitals and health care environments. The robots should communicate with elderly people, their families and caretakers…

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[Closed] Master Internship on Audio-visual speech separation using variational auto-encoders

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…

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[Closed] Master Internship on face alignment for audio-visual speech enhancement

In many audio-visual applications, e.g., speech enhancement and speech recognition, it is desirable to have aligned images of the mouth region such that a deep neural network can extract reliable visual features. Indeed, the quality of the extracted visual features impacts the performance of audio-visual based applications. In reality, however,…

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[Closed] Master Internship on Deep Speaker Recognition

Topic: Identification models have witnessed major improvements with the recent development of deep learning, especially when applied to the visual domain, contributing to the development of face-recognition [1] and person re-identification [2]. However,  comparable performances are yet to be achieved when applied to audio-based speaker recognition. Recent dataset assembling efforts…

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[Closed] Researcher on Deep and Reinforcement Learning for Robotics

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…

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[Closed] Engineer on Deep Learning and Cloud Computing

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…

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