Publications associées à A Kernel Trick For Sequences Applied to Text-Independent Speaker Verification Systems

Publications associées (30)

Overcoming Distribution Shifts and Imbalance Challenges in Representation Learning for Deep Regression Models

Deep learning has shown remarkable potential for industrial applications, particularly in predictive maintenance and condition monitoring. A key challenge in this domain is prognostics, specifically predicting the Remaining Useful Life (RUL) of assets - a ...

EPFL2025

Plasma state monitoring and disruption characterization using multimodal VAEs

Giulio Romanelli, Olivier Sauter, Alessandro Pau, Yoeri Renier Johannes Poels, Cristina Venturini

When a plasma disrupts in a tokamak, significant heat and electromagnetic loads are deposited onto the surrounding device components. These forces scale with plasma current and magnetic field strength, making disruptions one of the key challenges for futur ...

IOP Publishing Ltd2025

Scalable kernel logistic regression with Nyström approximation: Theoretical analysis and application to discrete choice modelling

Michel Bierlaire

The application of kernel-based Machine Learning (ML) techniques to discrete choice modelling using large datasets often faces challenges due to memory requirements and the considerable number of parameters involved in these models. This complexity hampers ...

2025

Bayes-optimal Learning of Deep Random Networks of Extensive-width

Lenka Zdeborová, Florent Gérard Krzakala, Hugo Chao Cui

We consider the problem of learning a target function corresponding to a deep, extensive-width, non-linear neural network with random Gaussian weights. We consider the asymptotic limit where the number of samples, the input dimension and the network width ...

2023

Exploiting Representation Similarities in Self-Supervised Learning for Vision Tasks

Thomas Grégoire Stegmüller

Recent progress in computer vision has been driven by a simple yet transformative observation: the potential of 30-year-old neural networks can be unlocked by massively scaling their parameters and the amount of human-labeled training data. This breakthrou ...

EPFL2025

End-to-end kernel learning via generative random Fourier features

Fanghui Liu

Random Fourier features (RFFs) provide a promising way for kernel learning in a spectral case. Current RFFs-based kernel learning methods usually work in a two-stage way. In the first-stage process, learn-ing an optimal feature map is often formulated as a ...

ELSEVIER SCI LTD2023

Weighting Pseudo-labels via High-Activation Feature Index Similarity and Object Detection for Semi-supervised Segmentation

Minh Hieu Lê

Semi-supervised semantic segmentation methods leverage unlabeled data by pseudo-labeling them. Thus the success of these methods hinges on the reliability of the pseudo-labels. Existing methods mostly choose high-confidence pixels in an effort to avoid err ...

Springer Science and Business Media Deutschland GmbH2025

Method and system for determining the intention of performing a voluntary action

Olaf Blanke, Oliver Alan Kannape, Hyeongdong Park, Bastien Orset

The invention relates to methods and systems for determining the intention of a subject to perform a voluntary action based on the analysis of the subject's respiratory phases and neuroelectrical signals. ...

2021

Analysis of Language Dependent Front-End for Speaker Recognition

Petr Motlicek, Subhadeep Dey

In Deep Neural Network (DNN) i-vector based speaker recognition systems, acoustic models trained for Automatic Speech Recognition are employed to estimate sufficient statistics for i-vector modeling. The DNN based acoustic model is typically trained on a w ...

ISCA-INT SPEECH COMMUNICATION ASSOC2018

Topics in Educational Cyber-Physical Labs : Configurations, Data Collection and Analysis

Wissam Halimi

Recent advances in remote sensing and actuation technologies, coupled with the large reach of the internet, allowed for the emergence of applications such as cyber-physical labs. Cyber-physical labs are the digital and remotely-accessible equivalent of the ...

EPFL2018

Learning Stable Task Sequences from Demonstration with Linear Parameter Varying Systems and Hidden Markov Models

Aude Billard

The problem of acquiring multiple tasks from demonstration is typi- cally divided in two sequential processes: (1) the segmentation or identification of different subgoals/subtasks and (2) a separate learning process that parameterizes a control policy for ...

robot-learning2017

Anomalies in Scheduling Control Applications and Design Complexity

Amir Aminifar

Today, many control applications in cyberphysical systems are implemented on shared platforms. Such resource sharing may lead to complex timing behaviors and, in turn, instability of control applications. This paper highlights a number of anomalies demonst ...

Ieee2017

Combining Electromyography and Tactile Myography to Improve Hand and Wrist Activity Detection in Prostheses

Sylvain Calinon, Noémie Laure Gwendoline Jaquier

Despite recent advances in prosthetics and assistive robotics in general, robust simultaneous and proportional control of dexterous prosthetic devices remains an unsolved problem, mainly because of inadequate sensorization. In this paper, we study the appl ...

2017

Acoustic and Lexical Resource Constrained ASR using Language-Independent Acoustic Model and Language-Dependent Probabilistic Lexical Model

Mathew Magimai Doss, Ramya Rasipuram

One of the key challenges involved in building statistical automatic speech recognition (ASR) systems is modeling the relationship between subword units or “lexical units” and acoustic feature observations. To model this relationship two types of resources ...

2015

Speaker diarization of spontaneous meeting room conversations

Sree Harsha Yella

Speaker diarization is the task of identifying ``who spoke when'' in an audio stream containing multiple speakers. This is an unsupervised task as there is no a priori information about the speakers. Diagnostical studies on state-of-the-art diarization sys ...

EPFL2015

On the Utility of Speech and Audio Foundation Models for Marmoset Call Analysis

Mathew Magimai Doss, Eklavya Sarkar

Marmoset monkeys encode vital information in their calls and serve as a surrogate model for neuro-biologists to understand the evolutionary origins of human vocal communication. Traditionally analyzed with signal processing-based features, recent approache ...

2024

System for predicting a prognosis of the neuropsychological and/or neuropsychiatric status in a subject

Olaf Blanke, Fosco Bernasconi

The present invention relates to systems and methods for predicting a prognosis of the neuropsychological and/or neuropsychiatric status in a subject based on reports of Minor Hallucination (MH) events in combination with electrophysiological data of the s ...

2024

The Movement Error Rate for Evaluation of Machine Learning Methods for sEMG-based Hand Movement Classification

Barbara Caputo

There has been increasing interest in applying learning algorithms to improve the dexterity of myoelectric prostheses. In this work, we present a large-scale benchmark evaluation on the second iteration of the publicly released NinaPro database, which cont ...

2014

Towards the Detection of AI-Synthesized Human Face Images

Touradj Ebrahimi, Yuhang Lu

Over the past years, image generation and manipulation have achieved remarkable progress due to the rapid development of generative AI based on deep learning. Recent studies have devoted significant efforts to address the problem of face image manipulation ...

2024

Scalable Probabilistic Models for Face and Speaker Recognition

Laurent El Shafey

In the biometrics community, face and speaker recognition are mature fields in which several systems have been proposed over the past twenty years. While existing systems perform well under controlled recording conditions, mismatch caused by the use of dif ...

EPFL2014