Publication

Speech/Music Discrimination using Entropy and Dynamism Features in a HMM Classification Framewor

Publications associées (73)

Graph Chatbot

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Connectez-vous pour utiliser Chat avec Graph Search

Robust audio segmentation

Jitendra Ajmera

Audio segmentation, in general, is the task of segmenting a continuous audio stream in terms of acoustically homogenous regions, where the rule of homogeneity depends on the task. This thesis aims at developing and investigating efficient, robust and unsup ...

EPFL2005

On Variable-Scale Piecewise Stationary Spectral Analysis of Speech Signals for ASR

Hervé Bourlard, Vivek Tyagi

It is often acknowledged that speech signals contain short-term and long-term temporal properties that are difficult to capture and model by using the usual fixed scale (typically 20ms) short time spectral analysis used in hidden Markov models (HMMs), base ...

IDIAP2005

Robust Audio Segmentation

Hervé Bourlard, Jitendra Ajmera

IDIAP2004

Robust Audio Segmentation

Hervé Bourlard, Jitendra Ajmera

École Polytechnique Fédérale de Lausanne2004

Music on the go: Catching the next growth opportunity for the music recording industry

Christopher Tucci

Catching the next growth opportunity for the music recording industry ...

2004

Spectral Entropy Based Feature for Robust ASR

Hervé Bourlard, Hynek Hermansky, Hemant Misra, Shajith Ikbal

In general, entropy gives us a measure of the number of bits required to represent some information. When applied to probability mass function (PMF), entropy can also be used to measure the ``peakiness'' of a distribution. In this paper, we propose using t ...

2004

Towards Robust and Adaptive Speech Recognition Models

Hervé Bourlard, Samy Bengio, Katrin Weber

In this paper, we discuss a family of new Automatic Speech Recognition (ASR) approaches, which somewhat deviate from the usual ASR approaches but which have recently been shown to be more robust to nonstationary noise, without requiring specific adaptation ...

Springer2004

Speech/Music Discrimination using Entropy and Dynamism Features in a HMM Classification Framework

Hervé Bourlard, Jitendra Ajmera

In this paper, we present a new approach towards high performance speech/music discrimination on realistic tasks related to the automatic transcription of broadcast news. In the approach presented here, the (local) Probability Density Function (PDF) estima ...

2003

HMM mixtures (HMM2) for robust speech recognition

Katrin Weber

State-of-the-art automatic speech recognition (ASR) techniques are typically based on hidden Markov models (HMMs) for the modeling of temporal sequences of feature vectors extracted from the speech signal. At the level of each HMM state, Gaussian mixture m ...

EPFL2003

HMM Mixtures (HMM2) for Robust Speech Recognition

Katrin Weber

Ecole Polytechnique Federale de Lausanne2003