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…
In signal processing and in computer vision, some of the most powerful tracking methods are based on the Kalman filter. The latter belongs to the unsupervised class of machine learning techniques and may well be viewed either as the simplest dynamic Bayesian network (DBN) or as a state-space model: it…
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…
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…
MSc project on “Speech enhancement with deep neural networks” Duration: about 6 months Short description: Speech enhancement [1] is an important preprocessing step to various speech information retrieval tasks such as automatic speech recognition. The goal of a speech enhancement method is to provide a clean speech signal from a noisy…
