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Towards ASR Based on Hierarchical Posterior-Based Keyword Recognition

Related publications (35)

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Hierarchical Multi-Stream Posterior Based Speech Recognition System

Hervé Bourlard, Samy Bengio, Hamed Ketabdar

In this paper, we present initial results towards boosting posterior based speech recognition systems by estimating more informative posteriors using multiple streams of features and taking into account acoustic context (e.g., as available in the whole utt ...

2005

Hierarchical Multi-Stream Posterior Based Speech Recognition System

Hervé Bourlard, Samy Bengio, Hamed Ketabdar

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

Hierarchical approach for spotting keywords

The paper presents a new approach to spotting a particular sound (keyword) in an acoustic stream. The approach is based on hierarchical processing where equally-sampled posterior probabilities of phoneme classes are estimated first, followed by matched fil ...

IDIAP2005

Posteriori Probabilities and Likelihoods Combination for Speech and Speaker Recognition

Hervé Bourlard

This paper investigates a new approach to perform simultaneous speech and speaker recognition. The likelihood estimated by a speaker identification system is combined with the posterior probability estimated by the speech recognizer. So, the joint posterio ...

IDIAP2004

Posteriori Probabilities and Likelihoods Combination for Speech and Speaker Recognition

Hervé Bourlard

2004

Modelling Auxiliary Features in Tandem Systems

Hervé Bourlard, Shajith Ikbal

Tandem systems transform the cepstral features into posterior probabilities of subword units using artificial neural networks (ANNs), which are processed to form input features for conventional speech recognition systems. They have been shown to perform be ...

2004

Modelling Auxiliary Features in Tandem Systems

Hervé Bourlard, Shajith Ikbal

IDIAP2004

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

On the Combination of Speech and Speaker Recognition

Hervé Bourlard

This paper investigates an approach that maximizes the joint posterior probabil ity of the pronounced word and the speaker identity given the observed data. This probability can be expressed as a product of the posterior probability of the pronounced word ...

IDIAP2003