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Confusion matrix based posterior probabilities correction

Publications associées (43)

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Pattern Recognition from One Example by Chopping

François Fleuret

We investigate the learning of the appearance of an object from a single image of it. Instead of using a large number of pictures of an object to be recognized, we use pictures of other objects to learn invariance to noise and variations in pose and illumi ...

2005

Spectral Entropy Feature in Multi-stream for Robust ASR

Hervé Bourlard, Hemant Misra

In recent papers, entropy computed from sub-bands of the spectrum was used as a feature for automatic speech recognition. In the present paper, we further study the sub-band spectral entropy features which can give the flatness/peakiness of the sub-band sp ...

IDIAP2005

Phase AutoCorrelation (PAC) features in Entropy based Multi-Stream for Robust Speech Recognition

Hervé Bourlard, Hynek Hermansky, Hemant Misra, Shajith Ikbal

Methods to improve noise robustness of speech recognition systems often result in degradation of recognition performance for clean speech. Recently proposed Phase AutoCorrelation (PAC) \cite{ikbal03,ikbal03a} based features, showing noticeable improvement ...

2004

Confusion Matrix Based Entropy Correction in Multi-stream Combination

Hemant Misra

An MLP classifier outputs a posterior probability for each class. With noisy data, classification becomes less certain, and the entropy of the posteriors distribution tends to increase providing a measure of classification confidence. However, at high nois ...

2003

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

On the Combination of Speech and Speaker Recognition

Hervé Bourlard

2003

Phase AutoCorrelation (PAC) features in Entropy based Multi-Stream for Robust Speech Recognition

Hervé Bourlard, Hynek Hermansky, Hemant Misra, Shajith Ikbal

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

Multi-stream adaptive evidence combination for noise robust ASR

Hervé Bourlard, Astrid Hagen

In this paper we develop different mathematical models in the framework of the multi-stream paradigm for noise robust ASR, and discuss their close relationship with human speech perception. Largely inspired by Fletcher's "product-of-errors" rule in psychoa ...

NORTH-HOLLAND2001

Using posterior probabilities for speech/music discrimination

Automatic speech/music discrimination has been receiving importance recently, for example when large multimedia documents have to be processed by an ASR system, or for indexing and retrieval of such documents. This work presents using outputs of a speech r ...

IDIAP2001