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Using more informative posterior probabilities for speech recognition

Publications associées (37)

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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 ...

IDIAP2005

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

Towards ASR Based on Hierarchical Posterior-Based Keyword Recognition

Hynek Hermansky

The paper presents an alternative approach to automatic recognition of speech in which each targeted word is classified by a separate binary classifier against all other sounds. No time alignment is done. To build a recognizer for N words, N parallel binar ...

IDIAP2005

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Local state or phone posterior probabilities are often investigated as local scores (e.g., hybrid HMM/ANN systems) or as transformed acoustic features (e.g., ``Tandem'') to improve speech recogni tion systems. In this paper, we present initial results towa ...

2005

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IDIAP2005

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

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

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

2004

Robust Audio Segmentation

Hervé Bourlard, Jitendra Ajmera

IDIAP2004