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Predicting Group Performance in Task-Based Interaction

Publications associées (34)

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Hilbert Envelope Based Features for Far-Field Speech Recognition

Hynek Hermansky, Sriram Ganapathy, Samuel Thomas

Automatic speech recognition (ASR) systems, trained on speech signals from close-talking microphones, generally fail in recognizing far-field speech. In this paper, we present a Hilbert Envelope based feature extraction technique to alleviate the artifacts ...

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

Novel speech processing techniques for robust automatic speech recognition

Vivek Tyagi

The goal of this thesis is to develop and design new feature representations that can improve the automatic speech recognition (ASR) performance in clean as well noisy conditions. One of the main shortcomings of the fixed scale (typically 20-30 ms long ana ...

EPFL2006

Using Pitch as Prior Knowledge in Template-Based Speech Recognition

Hervé Bourlard, Guillermo Aradilla

IDIAP2005

Speech Acquisition in Meetings with an Audio-Visual Sensor Array

Daniel Gatica-Perez, Darren Moore, Silèye Oumar Ba

Close-talk headset microphones have been traditionally used for speech acquisition in a number of applications, as they naturally provide a higher signal-to-noise ratio -needed for recognition tasks- than single distant microphones. However, in multi-party ...

IDIAP2005

Speech Acquisition in Meetings with an Audio-Visual Sensor Array

Daniel Gatica-Perez, Darren Moore, Silèye Oumar Ba

2005

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

Ecole Polytechnique Federale de Lausanne2003

HMM Mixtures (HMM2) for Robust Speech Recognition

Katrin Weber

IDIAP2003

A Pragmatic View of the Application of HMM2 for ASR

Hervé Bourlard, Samy Bengio, Katrin Weber

This report investigates the HMM2 approach recently introduced in the framework of automatic speech recognition. HMM2 can be seen as a mixture of HMMs, where a conventional primary HMM (processing a time series of speech data) is supported on a lower level ...

IDIAP2001