Publication

Towards a breakthrough Speaker Identification approach for Law Enforcement Agencies: SIIP

Publications associées (32)

Visual Speech Recognition Using PCA Networks and LSTMs in a Tandem GMM-HMM System

Jean-Philippe Thiran, Marina Zimmermann, Mostafa Mehdipour Ghazi

Automatic visual speech recognition is an interesting problem in pattern recognition especially when audio data is noisy or not readily available. It is also a very challenging task mainly because of the lower amount of information in the visual articulati ...

Springer International Publishing2016

Gender-specific attention system subnetwork vulnerability in prematurely born children

Jean-Philippe Thiran, Elda Fischi Gomez

Children born prematurely are at high risk for long-term abnormal development, including deficits in attentional abilities that persist throughout adolescence. The severity of these cognitive difficulties varies significantly among preterm-born children, w ...

2016

Science and Engineering Ph.D. Students’ Career Outcomes, by Gender

Fabiana Visentin, Annamaria Conti

We examine differences in the careers of men and women Ph.D.s from two major European universities. Having performed regression analysis, we find that women are more likely than men to be employed in public administration when the alternatives are either a ...

Public Library of Science2015

EMPLOYMENT OF SUBSPACE GAUSSIAN MIXTURE MODELS IN SPEAKER RECOGNITION

Petr Motlicek, Subhadeep Dey

This paper presents Subspace Gaussian Mixture Model (SGMM) approach employed as a probabilistic generative model to estimate speaker vector representations to be subsequently used in the speaker verification task. SGMMs have already been shown to significa ...

2015

EMPLOYMENT OF SUBSPACE GAUSSIAN MIXTURE MODELS IN SPEAKER RECOGNITION

Petr Motlicek, Subhadeep Dey

Idiap2015

Combining Vocal Tract Length Normalization with Hierarchical Linear Transformations

Philip Neil Garner, John David Scott Dines, Lakshmi Babu Saheer

Recent research has demonstrated the effectiveness of vocal tract length normalization (VTLN) as a rapid adaptation technique for statistical parametric speech synthesis. VTLN produces speech with naturalness preferable to that of MLLR-based adaptation tec ...

2014

Posterior-based Sparse Representation for Automatic Speech Recognition

Hervé Bourlard, Afsaneh Asaei, David Imseng, Sara Bahaadini Beigy Zarandi

Posterior features have been shown to yield very good performance in multiple contexts including speech recognition, spoken term detection, and template matching. These days, posterior features are usually estimated at the output of a neural network. More ...

2014

Visual masking deficits in healthy and schizophrenic women

Michael Herzog, Maya Roinishvili

Schizophrenic patients have serious visual masking deficits which are likely related to the genetic underpinnings of the disease because also unaffected relatives of the patients show masking deficits. We presented a left/right offset vernier followed by a ...

2013

Unified Framework of Feature Based Adaptation for Statistical Speech Synthesis and Recognition

Lakshmi Babu Saheer

The advent of statistical parametric speech synthesis has paved new ways to a unified framework for hidden Markov model (HMM) based text to speech synthesis (TTS) and automatic speech recognition (ASR). The techniques and advancements made in the field of ...

EPFL2013

Dynamic Classifier Fusion for Multi-sensory Activity Recognition

Hesam Sagha

Nowadays, many systems rely on fusing different sources of information to recognize human activities and gestures, speech, or brain activities for applications in areas such as clinical practice, and health care and Human Computer Interaction (HCI). Typica ...

EPFL2013

Graph Chatbot

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Connectez-vous pour utiliser Chat avec Graph Search