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Publications associées (7)

On Learning to Identify Genders from Raw Speech Signal Using CNNs

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

280 Birds with One Stone: Inducing Multilingual Taxonomies from Wikipedia Using Character-Level Classification

Karl Aberer, Rémi Philippe Lebret, Hamza Harkous, Amit Gupta

We propose a novel fully-automated approach towards inducing multilingual taxonomies fromWikipedia. Given an English taxonomy, our approach first leverages the interlanguage links of Wikipedia to automatically construct training datasets for the is-a relat ...

ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE2018

Word pair classification during imagined speech using direct brain recordings

José del Rocio Millán Ruiz, Inaki Asier Iturrate Gil, Stéphanie Martin

People that cannot communicate due to neurological disorders would benefit from an internal speech decoder. Here, we showed the ability to classify individual words during imagined speech from electrocorticographic signals. In a word imagery task, we used ...

Nature Research2016

n-Stabilizing bisets

Alex Monnard

One generalises the notion of stabilizing bisets from [BouThe] to n-stabilizing bisets. This allows us to find new examples of stabilization for Roquette groups. We first investigate the idea of n-stabilizing bisets. We give a way to construct examples wit ...

2014

Understanding the Web

Eda Baykan

The World Wide Web is one of the most widely used information resources. Understanding the web better will enable us to benefit more of it. In this thesis we develop techniques to learn the properties of the web pages like language and topic using only the ...

EPFL2009

Web page language identification based on URLs

Monika Henzinger, Ingmar Weber, Eda Baykan

Given only the URL of a web page, can we identify its language? This is the question that we examine in this paper. Such a language classifier is, for example, useful for crawlers of web search engines, which frequently try to satisfy certain language quot ...

2008

Using auxiliary sources of knowledge for automatic speech recognition

Mathew Magimai Doss

Standard hidden Markov model (HMM) based automatic speech recognition (ASR) systems usually use cepstral features as acoustic observation and phonemes as subword units. Speech signal exhibits wide range of variability such as, due to environmental variatio ...

EPFL2005