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HMM Mixtures (HMM2) for Robust Speech Recognition

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On Factorizing Spectral Dynamics for Robust Speech Recognition

Hervé Bourlard, Hemant Misra, Vivek Tyagi

In this paper, we introduce new dynamic speech features based on the modulation spectrum. These features, termed Mel-cepstrum Modulation Spectrum (MCMS), map the time trajectories of the spectral dynamics into a series of slow and fast moving orthogonal co ...

IDIAP2003

On Factorizing Spectral Dynamics for Robust Speech Recognition

Hervé Bourlard, Hemant Misra, Vivek Tyagi

2003

HMM inference towards flexible speech recognition

One of the difficulties in Automatic Speech Recognizer (ASR) is the pronunciation variability. Each word (modeled by a baseline phonetic transcription in the ASR dictionary) can be pronounced in many different ways depending on many complex qualitative and ...

IDIAP2003

Using pitch frequency information in speech recognition

Hervé Bourlard

Automatic Speech Recognition systems typically use smoothed spectral features as acoustic observations. In recent studies, it has been shown that complementing these standard features with pitch frequency could improve the system performance of the system. ...

IDIAP2003

Using pitch frequency information in speech recognition

Hervé Bourlard

2003

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 ...

IDIAP2003

Gaussian mixture models for on-line signature verification

Jonas Richiardi, Andrzej Drygajlo

This paper introduces and motivates the use of Gaussian Mixture Models (GMMs) for on-line signature verification. The individual Gaussian components are shown to represent some local, signer-dependent features that characterise spatial and temporal aspects ...

2003

Speaker Normalization using HMM2

Hervé Bourlard, Katrin Weber, Shajith Ikbal

In this paper, we present an HMM2 based method for speaker normalization. Introduced as an extension of Hidden Markov Model (HMM), HMM2 differentiates itself from the regular HMM in terms of the emission density modeling, which is done by a set of state-de ...

IDIAP2002

Speaker Normalization using HMM2

Hervé Bourlard, Katrin Weber, Shajith Ikbal

2002

User-Customized Password Speaker Verification based on HMM/ANN and GMM Models

Hervé Bourlard

In this paper, we present a new approach towards user-custom-ized password speaker verification combining the advantages of hybrid HMM/ANN systems, using Artificial Neural Networks (ANN) to estimate emission probabilities of Hidden Markov Models, and Gaus ...

IDIAP2002