Publications related to A Unified Framework for Score Normalization Techniques Applied to Text Independent Speaker Verification

Novel Methods For Detection And Analysis Of Atypical Aspects In Speech

Atypical aspects in speech concern speech that deviates from what is commonly considered normal or healthy. In this thesis, we propose novel methods for detection and analysis of these aspects, e.g. to monitor the temporary state of a speaker, diseases tha ...

EPFL2023

A Virtual Simulation-Pilot Agent for Training of Air Traffic Controllers

Petr Motlicek, Amrutha Prasad, Juan Pablo Zuluaga Gomez

In this paper we propose a novel virtual simulation-pilot engine for speeding up air traffic controller (ATCo) training by integrating different state-of-the-art artificial intelligence (AI)-based tools. The virtual simulation-pilot engine receives spoken ...

MDPI2023

Automatic pathological speech assessment

Parvaneh Janbakhshi

Many pathologies cause impairments in the speech production mechanism resulting in reduced speech intelligibility and communicative ability. To assist the clinical diagnosis, treatment and management of speech disorders, automatic pathological speech asses ...

EPFL2022

Utterance Verification-Based Dysarthric Speech Intelligibility Assessment Using Phonetic Posterior Features

Mathew Magimai Doss, Julian David Fritsch

In the literature, the task of dysarthric speech intelligibility assessment has been approached through development of different low-level feature representations, subspace modeling, phone confidence estimation or measurement of automatic speech recognitio ...

IEEE Institute of Electrical and Electronics Engineers2021

Word-level Embeddings for Cross-Task Transfer Learning in Speech Processing

Pierre Anton Beckmann, Milos Cernak

Recent breakthroughs in deep learning often rely on representation learning and knowledge transfer. In recent years, unsupervised and self-supervised techniques for learning speech representation were developed to foster automatic speech recognition. Up to ...

EUROPEAN ASSOC SIGNAL SPEECH & IMAGE PROCESSING-EURASIP2021

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

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

Towards directly modeling raw speech signal for speaker verification using CNNs

Sébastien Marcel, Hannah Muckenhirn

Speaker verification systems traditionally extract and model cepstral features or filter bank energies from the speech signal. In this paper, inspired by the success of neural network-based approaches to model directly raw speech signal for applications su ...

IEEE2018

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

Combining Multiple Views for Visual Speech Recognition

Jean-Philippe Thiran, Marina Zimmermann, Mostafa Mehdipour Ghazi, Hazim Kemal Ekenel

Visual speech recognition is a challenging research problem with a particular practical application of aiding audio speech recognition in noisy scenarios. Multiple camera setups can be beneficial for the visual speech recognition systems in terms of improv ...

KTH2017

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

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

Articulatory feature based continuous speech recognition using probabilistic lexical modeling

Mathew Magimai Doss, Ramya Rasipuram

Phonological studies suggest that the typical subword units such as phones or phonemes used in automatic speech recognition systems can be decomposed into a set of features based on the articulators used to produce the sound. Most of the current approaches ...

Elsevier2016

Joint Speaker Verification and Anti-Spoofing in the i-Vector Space

Sébastien Marcel

Any biometric recognizer is vulnerable to spoofing attacks and hence voice biometric, also called automatic speaker verification (ASV), is no exception; replay, synthesis, and conversion attacks all provoke false acceptances unless countermeasures are used ...

2015

Robust Log-Energy Estimation and its Dynamic Change Enhancement for In-car Speech Recognition

Hervé Bourlard, Weifeng Li

The log-energy parameter, typically derived from a full-band spectrum, is a critical feature commonly used in automatic speech recognition (ASR) systems. However, log-energy is difficult to estimate reliably in the presence of background noise. In this pap ...

Ieee-Inst Electrical Electronics Engineers Inc2013

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

Multi-pose lipreading and audio-visual speech recognition

Jean-Philippe Thiran, Virginia Estellers Casas

In this article, we study the adaptation of visual and audio-visual speech recognition systems to non-ideal visual conditions. We focus on overcoming the effects of a changing pose of the speaker, a problem encountered in natural situations where the speak ...

2012

Cross-pollination of normalisation techniques from speaker to face authentication using Gaussian mixture models

Sébastien Marcel

This paper applies score and feature normalization techniques to parts-based Gaussian mixture model (GMM) face authentication. In particular, we propose to utilize techniques that are well established in state-of-the-art speaker authentication, and apply t ...

2012

Boosting Localized Features for Speaker and Speech Recognition

Anindya Roy

In this thesis, we propose a novel approach for speaker and speech recognition involving localized, binary, data-driven features. The proposed approach is largely inspired by similar localized approaches in the computer vision domain. The success of these ...

EPFL2011

Overcoming Asynchrony in Audio-Visual Speech Recognition

Jean-Philippe Thiran, Virginia Estellers Casas

In this paper we propose two alternatives to overcome the natural asynchrony of modalities in Audio-Visual Speech Recognition. We first investigate the use of asynchronous statistical models based on Dynamic Bayesian Networks with different levels of async ...

2010