Publication

Automatic Recognition of Emergent Social Roles in Small Group Interactions

Related publications (25)

Robust Outlier Rejection for 3D Registration with Variational Bayes

Mathieu Salzmann, Zheng Dang, Zhen Wei, Jiancheng Yang, Haobo Jiang

Learning-based outlier (mismatched correspondence) rejection for robust 3D registration generally formulates the outlier removal as an inlier/outlier classification problem. The core for this to be successful is to learn the discriminative inlier/outlier f ...

Ieee Computer Soc2023

Explanation of Face Recognition via Saliency Maps

Touradj Ebrahimi, Yuhang Lu

Despite the significant progress in recent years, deep face recognition is often treated as a "black box" and has been criticized for lacking explainability. It becomes increasingly important to understand the characteristics and decisions of deep face rec ...

2023

How to Boost Face Recognition with StyleGAN?

Nikita Durasov

State-of-the-art face recognition systems require vast amounts of labeled training data. Given the priority of privacy in face recognition applications, the data is limited to celebrity web crawls, which have issues such as limited numbers of identities. O ...

Ieee Computer Soc2023

A Two-Step Approach To Leverage Contextual Data: Speech Recognition In Air-Traffic Communications

Petr Motlicek, Amrutha Prasad, Juan Pablo Zuluaga Gomez

Automatic Speech Recognition (ASR), as the assistance of speech communication between pilots and air-traffic controllers, can significantly reduce the complexity of the task and increase the reliability of transmitted information. ASR application can lead ...

IEEE2022

On quantifying the quality of acoustic models in hybrid DNN-HMM ASR

Hervé Bourlard, Afsaneh Asaei, Pranay Dighe

We propose an information theoretic framework for quantitative assessment of acoustic models used in hidden Markov model (HMM) based automatic speech recognition (ASR). The HMM backend expects that (i) the acoustic model yields accurate state conditional e ...

ELSEVIER2020

End-to-End Acoustic Modeling using Convolutional Neural Networks for HMM-based Automatic Speech Recognition

Mathew Magimai Doss, Dimitri Palaz, Ronan Collobert

In hidden Markov model (HMM) based automatic speech recognition (ASR) system, modeling the statistical relationship between the acoustic speech signal and the HMM states that represent linguistically motivated subword units such as phonemes is a crucial st ...

ELSEVIER SCIENCE BV2019

Method of handwritten character recognition confirmation

Thibault Lucien Christian Asselborn, Wafa Monia Benkaouar Johal

The present invention concerns a method for an artificial neural network to confirm the recognition of handwritten characters produced by a user. The method comprising: training (21) the artificial neural network with a training data set comprising a first ...

2019

GestureGAN for Hand Gesture-to-Gesture Translation in the Wild

Yan Yan, Wei Wang

Hand gesture-to-gesture translation in the wild is a challenging task since hand gestures can have arbitrary poses, sizes, locations and self-occlusions. Therefore, this task requires a high-level understanding of the mapping between the input source gestu ...

ASSOC COMPUTING MACHINERY2018

On Learning to Identify Genders from Raw Speech Signal Using CNNs

Hannah Muckenhirn, Selen Hande Kabil

Automatic Gender Recognition (AGR) is the task of identifying the gender of a speaker given a speech signal. Standard approaches extract features like fundamental frequency and cepstral features from the speech signal and train a binary classifier. Inspire ...

ISCA-INT SPEECH COMMUNICATION ASSOC2018

Variational Methods for Human Modeling

Timur Bagautdinov

A large part of computer vision research is devoted to building models and algorithms aimed at understanding human appearance and behaviour from images and videos. Ultimately, we want to build automated systems that are at least as capable as people when i ...

EPFL2018

Template-matching for text-dependent speaker verification

Petr Motlicek, Subhadeep Dey

In the last decade, i-vector and Joint Factor Analysis (JFA) approaches to speaker modeling have become ubiquitous in the area of automatic speaker recognition. Both of these techniques involve the computation of posterior probabilities, using either Gauss ...

2017

Multi-Modal Mean-Fields via Cardinality-Based Clamping

Pascal Fua, François Fleuret

Mean Field inference is central to statistical physics. It has attracted much interest in the Computer Vision community to efficiently solve problems expressible in terms of large Conditional Random Fields. However, since it models the posterior probabilit ...

Ieee2017

Role of SEC62 in ER maintenance: A link with ER stress tolerance in SEC62-overexpressing tumors?

Maurizio Molinari

Amplification of the candidate oncogene TLOC1/SEC62 in tumors correlates with reduced patient survival. The recently reported role of SEC62 as an autophagy receptor that controls endoplasmic reticulum (ER) size and function might open new scenarios for und ...

Taylor & Francis Inc2017

INTRA-CLASS COVARIANCE ADAPTATION IN PLDA BACK-ENDS FOR SPEAKER VERIFICATION

Petr Motlicek, Subhadeep Dey

Multi-session training conditions are becoming increasingly common in recent benchmark datasets for both text-independent and text-dependent speaker verification. In the state-of-the-art i-vector framework for speaker verification, such conditions are addr ...

Ieee2017

Long-Term Spectral Statistics for Voice Presentation Attack Detection

Mathew Magimai Doss, Sébastien Marcel, Hannah Muckenhirn

Automatic speaker verification systems can be spoofed through recorded, synthetic or voice converted speech of target speakers. To make these systems practically viable, the detection of such attacks, referred to as presentation attacks, is of paramount in ...

2017

Towards End-to-End Speech Recognition

Dimitri Palaz

Standard automatic speech recognition (ASR) systems follow a divide and conquer approach to convert speech into text. Alternately, the end goal is achieved by a combination of sub-tasks, namely, feature extraction, acoustic modeling and sequence decoding, ...

EPFL2016

Trustworthy Biometric Verification under Spoofing Attacks : Application to the Face Mode

Ivana Chingovska

The need for automation of the identity recognition process for a vast number of applications resulted in great advancement of biometric systems in the recent years. Yet, many studies indicate that these systems suffer from vulnerabilities to spoofing (pre ...

EPFL2016

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

Embedding Local Quality Measures in Minutiae-Based Biometric Recognition

Mohammad Hamed Izadi

Degradation in data quality is still a main source of errors in the modern biometric recognition systems. However, the data quality can be embedded in the recognition methods at global and local levels to build more accurate biometric systems. Local qualit ...

EPFL2016

A leap of faith in the realm of the possible

Caroline Dionne

The architectural projects and building operations conducted over the past three decades by Patrick Bouchain and his collaborators challenge a series of assumptions regarding architecture’s authorship, its purpose and usage. Examined in light of Paul Ricoe ...

2016