Publications related to Entropy Based Combination of Tandem Representations for Noise Robust ASR

Entropy Based Combination of Tandem Representations for Noise Robust ASR

Hervé Bourlard, Hynek Hermansky, Hemant Misra, Shajith Ikbal

In this paper, we present an entropy based method to combine tandem representations of the recently proposed Phase AutoCorrelation (PAC) based features and Mel-Frequency Cepstral Coefficients (MFCC) features. PAC based features, derived from a nonlinear tr ...

IDIAP2004

An Investigation of Spectral Subband Centroids for Speaker Authentication

Samy Bengio, Norman Hoon Thian Poh

Most conventional features used in speaker authentication are based on estimation of spectral envelopes in one way or another, in the form of cepstrums, e.g., Mel-scale Filterbank Cepstrum Coefficients (MFCCs), Linear-scale Filterbank Cepstrum Coefficients ...

2004

Multi-resolution Spectral Entropy Based Feature for Robust ASR

Hervé Bourlard, Hemant Misra, Shajith Ikbal

Recently, entropy measures at different stages of recognition have been used in automatic speech recognition (ASR) task. In a recent paper, we proposed that formant positions of a spectrum can be captured by multi-resolution spectral entropy feature. In th ...

IDIAP2004

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

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 ...

Ecole Polytechnique Federale de Lausanne2003

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 ...

IDIAP2003

Nonlinear Spectral Transformations for Robust Speech Recognition

Hervé Bourlard, Hynek Hermansky, Shajith Ikbal

Recently, a nonlinear transformation of autocorrelation coefficients named Phase AutoCorrelation (PAC) coefficients has been considered for feature extraction \cite{ikbal03}. PAC based features show improved robustness to additive noise as a result of two ...

IDIAP2003

Nonlinear Spectral Transformations for Robust Speech Recognition

Hervé Bourlard, Hynek Hermansky, Shajith Ikbal

Recently, a nonlinear transformation of autocorrelation coefficients named Phase AutoCorrelation (PAC) coefficients has been considered for feature extraction \cite{ikbal03}. PAC based features show improved robustness to additive noise as a result of two ...

2003

An Investigation of Spectral Subband Centroids for Speaker Authentication

Samy Bengio, Norman Hoon Thian Poh

Most conventional features used in speaker authentication are based on estimation of spectral envelopes in one way or another, in the form of cepstrums, e.g., Mel-scale Filterbank Cepstrum Coefficients (MFCCs), Linear-scale Filterbank Cepstrum Coefficients ...

IDIAP2003

Entropy-based Multi-stream Combination

Hervé Bourlard, Hemant Misra, Vivek Tyagi

Full-combination multi-band approach has been proposed in the literature and performs well for band-limited noise. But the approach fails to deliver in case of wide-band noise. To overcome this, multi-stream approaches are proposed in literature with varyi ...

IDIAP2002

Entropy Based Combination of Tandem Representations for Noise Robust ASR

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Entropy Based Combination of Tandem Representations for Noise Robust ASR

An Investigation of Spectral Subband Centroids for Speaker Authentication

Multi-resolution Spectral Entropy Based Feature for Robust ASR

HMM mixtures (HMM2) for robust speech recognition

HMM Mixtures (HMM2) for Robust Speech Recognition

HMM Mixtures (HMM2) for Robust Speech Recognition

Nonlinear Spectral Transformations for Robust Speech Recognition

Nonlinear Spectral Transformations for Robust Speech Recognition

An Investigation of Spectral Subband Centroids for Speaker Authentication

Entropy-based Multi-stream Combination

HMM Mixtures (HMM2) for Robust Speech Recognition

HMM mixtures (HMM2) for robust speech recognition

HMM Mixtures (HMM2) for Robust Speech Recognition

Entropy-based Multi-stream Combination

An Investigation of Spectral Subband Centroids for Speaker Authentication

An Investigation of Spectral Subband Centroids for Speaker Authentication

Nonlinear Spectral Transformations for Robust Speech Recognition

Entropy Based Combination of Tandem Representations for Noise Robust ASR

Multi-resolution Spectral Entropy Based Feature for Robust ASR

Nonlinear Spectral Transformations for Robust Speech Recognition