Publications related to ROXANNE Research Platform: Automate criminal investigations

Sparse Autoencoders for Speech Modeling and Recognition

Speech recognition-based applications upon the advancements in artificial intelligence play an essential role to transform most aspects of modern life. However, speech recognition in real-life conditions (e.g., in the presence of overlapping speech, varyin ...

EPFL2023

Impact of Video Processing Operations in Deepfake Detection

Touradj Ebrahimi, Yuhang Lu

The detection of digital face manipulation in video has attracted extensive attention due to the increased risk to public trust. To counteract the malicious usage of such techniques, deep learning-based deepfake detection methods have been developed and ha ...

2023

Methodology for selecting measurement points that optimize information gain for model updating

Ian Smith, Numa Joy Bertola

Information collected through sensor measurements has the potential to improve knowledge of complex-system behavior, leading to better decisions related to system management. In this situation, and particularly when using digital twins, the quality of sens ...

2023

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

Low-Power Artificial Neural Network Perceptron Based on Monolayer MoS2

Andras Kis, Aleksandra Radenovic, Zhenyu Wang, Guilherme Migliato Marega, Mukesh Kumar Tripathi

Machine learning and signal processing on the edge are poised to influence our everyday lives with devices that will learn and infer from data generated by smart sensors and other devices for the Internet of Things. The next leap toward ubiquitous electron ...

2022

How Does Pre-Trained Wav2Vec 2.0 Perform On Domain-Shifted Asr? An Extensive Benchmark On Air Traffic Control Communications

Petr Motlicek, Amrutha Prasad, Juan Pablo Zuluaga Gomez

Recent work on self-supervised pre-training focus on leveraging large-scale unlabeled speech data to build robust end-to-end (E2E) acoustic models (AM) that can be later fine-tuned on downstream tasks e.g., automatic speech recognition (ASR). Yet, few work ...

IEEE2022

Automatic Call Sign Detection: Matching Air Surveillance Data with Air Traffic Spoken Communications

Petr Motlicek, Amrutha Prasad

Voice communication is the main channel to exchange information between pilots and Air-Traffic Controllers (ATCos). Recently, several projects have explored the employment of speech recognition technology to automatically extract spoken key information suc ...

MDPI2021

Multitask adaptation with Lattice-Free MMI for multi-genre speech recognition of low resource languages

Hervé Bourlard, Petr Motlicek

In this paper, we develop Automatic Speech Recognition (ASR) systems for multi-genre speech recognition of low-resource languages where training data is predominantly conversational speech but test data can be in one of the following genres: news broadcast ...

ISCA-INT SPEECH COMMUNICATION ASSOC2021

Fair Voice Biometrics: Impact of Demographic Imbalance on Group Fairness in Speaker Recognition

Mirko Marras

Speaker recognition systems are playing a key role in modern online applications. Though the susceptibility of these systems to discrimination according to group fairness metrics has been recently studied, their assessment has been mainly focused on the di ...

ISCA-INT SPEECH COMMUNICATION ASSOC2021

Feedback and Common Information: Bounds and Capacity for Gaussian Networks

Erixhen Sula

Network information theory studies the communication of information in a network and considers its fundamental limits. Motivating from the extensive presence of the networks in the daily life, the thesis studies the fundamental limits of particular network ...

EPFL2021

Novel Methods for Incorporating Prior Knowledge for Automatic Speech Assessment

Subrahmanya Pavankumar Dubagunta

Speech signal conveys several kinds of information such as a message, speaker identity, emotional state of the speaker and social state of the speaker. Automatic speech assessment is a broad area that refers to using automatic methods to predict human judg ...

EPFL2021

Deep Learning Approaches for Auditory Perception in Robotics

Weipeng He

Auditory perception is an essential part of a robotic system in Human-Robot Interaction (HRI), and creating an artificial auditory perception system that is on par with human has been a long-standing goal for researchers. In fact, this is a challenging res ...

EPFL2021

Statistical limits of high-dimensional inference problems

Clément Dominique Luneau

This thesis focuses on two kinds of statistical inference problems in signal processing and data science. The first problem is the estimation of a structured informative tensor from the observation of a noisy tensor in which it is buried. The structure com ...

EPFL2021

Graph Signal Processing for Machine Learning: A Review and New Perspectives

Pascal Frossard, Ntorina Thanou, Xiaowen Dong, Laura Toni, Michael Bronstein

The effective representation, processing, analysis, and visualization of large-scale structured data, especially those related to complex domains, such as networks and graphs, are one of the key questions in modern machine learning. Graph signal processing ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Multilingual Training and Adaptation in Speech Recognition

Sibo Tong

State-of-the-art acoustic models for Automatic Speech Recognition (ASR) are based on Hidden Markov Models (HMM) and Deep Neural Networks (DNN) and often require thousands of hours of transcribed speech data during training. Therefore, building multilingual ...

EPFL2020

ExprADA: Adversarial domain adaptation for facial expression analysis

Jean-Philippe Thiran, Seyedbehzad Bozorgtabar

We propose a deep neural network based image-to-image translation for domain adaptation, which aims at finding translations between image domains. Despite recent GAN based methods showing promising results in image-to-image translation, they are prone to f ...

2020

Mixed-Precision Deep Learning Based on Computational Memory

Irem Boybat Kara, Abu Sebastian, Evangelos Eleftheriou

Deep neural networks (DNNs) have revolutionized the field of artificial intelligence and have achieved unprecedented success in cognitive tasks such as image and speech recognition. Training of large DNNs, however, is computationally intensive and this has ...

FRONTIERS MEDIA SA2020

Dynamic pattern recognition in large-scale graphs with applications to social networks

Volodymyr Miz

A graph is a versatile data structure facilitating representation of interactions among objects in various complex systems. Very often these objects have attributes whose measurements change over time, reflecting the dynamics of the system. This general da ...

EPFL2020

A Real-Time Multi-Camera Depth Estimation ASIC with Custom On-Chip Embedded DRAM

Jonathan Emmanuel D Narinx

The capability to process high-resolution videos in real-time is becoming more important in a wide variety of applications such as autonomous vehicles, virtual reality or intelligent surveillance systems. The high-accuracy and complex video processing algo ...

EPFL2019

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