Publications related to Combining Vocal Tract Length Normalization with Linear Transformations in a Bayesian Framework

Acoustic models for posterior features in speech recognition

In this thesis, we investigate the use of posterior probabilities of sub-word units directly as input features for automatic speech recognition (ASR). These posteriors, estimated from data-driven methods, display some favourable properties such as increase ...

EPFL2008

Acoustic Models for Posterior Features in Speech Recognition

Guillermo Aradilla

In this thesis, we investigate the use of posterior probabilities of sub-word units directly as input features for automatic speech recognition (ASR). These posteriors, estimated from data-driven methods, display some favourable properties such as increase ...

Ecole Polytechnique Fédérale de Lausanne2008

Acoustic Models for Posterior Features in Speech Recognition

Guillermo Aradilla

In this thesis, we investigate the use of posterior probabilities of sub-word units directly as input features for automatic speech recognition (ASR). These posteriors, estimated from data-driven methods, display some favourable properties such as increase ...

Idiap2008

Using Pitch as Prior Knowledge in Template-Based Speech Recognition

Hervé Bourlard, Guillermo Aradilla

In a previous paper on speech recognition, we showed that templates can better capture the dynamics of speech signal compared to parametric models such as hidden Markov models. The key point in template matching approaches is finding the most similar templ ...

2006

Using more informative posterior probabilities for speech recognition

Hervé Bourlard, Samy Bengio, Hamed Ketabdar

In this paper, we present initial investigations towards boosting posterior probability based speech recognition systems by estimating more informative posteriors taking into account acoustic context (e.g., the whole utterance), as well as possible prior i ...

2006

Speaker recognition in noisy environments using auxiliary information and Bayesian networks

Speaker recognition systems achieve acceptable performance in controlled laboratory conditions. However, in real-life environments, the performance of a speaker recognition system degrades drastically, the principal cause being the mismatch that exists bet ...

EPFL2006

Using Pitch as Prior Knowledge in Template-Based Speech Recognition

Hervé Bourlard, Guillermo Aradilla

In a previous paper on speech recognition, we showed that templates can better capture the dynamics of speech signal compared to parametric models such as hidden Markov models. The key point in template matching approaches is finding the most similar templ ...

IDIAP2005

Continuous Microphone Array Speech Recognition on Wall Street Journal Corpus

Hervé Bourlard

In this paper, we present a robust speech acquisition system to acquire continuous speech using a microphone array. A microphone array based speech recognition system is also presented to study the environmental interference due to reverberation, backgroun ...

IDIAP2005

Using more informative posterior probabilities for speech recognition

Hervé Bourlard, Samy Bengio, Hamed Ketabdar

In this paper, we present initial investigations towards boosting posterior probability based speech recognition systems by estimating more informative posteriors taking into account acoustic context (e.g., the whole utterance), as well as possible prior i ...

IDIAP2005

Towards using hierarchical posteriors for flexible automatic speech recognition systems

Hervé Bourlard, Samy Bengio, Bertrand Mesot

Local state (or phone) posterior probabilities are often investigated as local classifiers (e.g., hybrid HMM/ANN systems) or as transformed acoustic features (e.g., ``Tandem'') towards improved speech recognition systems. In this paper, we present initial ...

IDIAP2004

Combining Vocal Tract Length Normalization with Linear Transformations in a Bayesian Framework

Acoustic models for posterior features in speech recognition

Acoustic Models for Posterior Features in Speech Recognition

Acoustic Models for Posterior Features in Speech Recognition

Using Pitch as Prior Knowledge in Template-Based Speech Recognition

Using more informative posterior probabilities for speech recognition

Speaker recognition in noisy environments using auxiliary information and Bayesian networks

Using Pitch as Prior Knowledge in Template-Based Speech Recognition

Continuous Microphone Array Speech Recognition on Wall Street Journal Corpus

Using more informative posterior probabilities for speech recognition

Towards using hierarchical posteriors for flexible automatic speech recognition systems

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Acoustic Models for Posterior Features in Speech Recognition

Using Pitch as Prior Knowledge in Template-Based Speech Recognition

Using more informative posterior probabilities for speech recognition

Continuous Microphone Array Speech Recognition on Wall Street Journal Corpus

Speaker recognition in noisy environments using auxiliary information and Bayesian networks

Acoustic models for posterior features in speech recognition

Acoustic Models for Posterior Features in Speech Recognition

Towards using hierarchical posteriors for flexible automatic speech recognition systems

Using more informative posterior probabilities for speech recognition

Using Pitch as Prior Knowledge in Template-Based Speech Recognition