Concept

Classifier (linguistics)

Related publications (15)

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

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 from Wikipedia. Given an English taxonomy, our approach first leverages the interlanguage links of Wikipedia to automatically construct training datasets for the is-a rela ...

arxiv.org2017

Sound Pattern Matching for Automatic Prosodic Event Detection

Hervé Bourlard, Philip Neil Garner, Milos Cernak, Afsaneh Asaei, Pierre-Edouard Jean Charles Honnet

Prosody in speech is manifested by variations of loudness, exaggeration of pitch, and specific phonetic variations of prosodic segments. For example, in the stressed and unstressed syllables, there are differences in place or manner of articulation, vowels ...

Idiap2016

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 Publishing Group2016

Improving Grapheme-based ASR by Probabilistic Lexical Modeling Approach

Ramya Rasipuram

There is growing interest in using graphemes as subword units, especially in the context of the rapid development of hidden Markov model (HMM) based automatic speech recognition (ASR) system, as it eliminates the need to build a phoneme pronunciation lexic ...

2013

Improving Grapheme-based ASR by Probabilistic Lexical Modeling Approach

Ramya Rasipuram

Idiap2013

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

Unsupervised Speech/Non-speech Detection for Automatic Speech Recognition in Meeting Rooms

Daniel Gatica-Perez, Petr Motlicek

The goal of this work is to provide robust and accurate speech detection for automatic speech recognition (ASR) in meeting room settings. The solution is based on computing long-term modulation spectrum, and examining specific frequency range for dominant ...

2007

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