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Some applications of a priori knowledge in multi-stream HMM and HMM/ANN based ASR

Publications associées (96)

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On Variable-Scale Piecewise Stationary Spectral Analysis of Speech Signals for ASR

Hervé Bourlard, Vivek Tyagi

It is often acknowledged that speech signals contain short-term and long-term temporal properties that are difficult to capture and model by using the usual fixed scale (typically 20ms) short time spectral analysis used in hidden Markov models (HMMs), base ...

IDIAP2005

Automatic Speech Receognition for Human-Machine Interaction

Pierre-André Farine, Michael Ansorge, Sara Grassi Pauletti

Since the sixties, movies such as “2001: A Space Odyssey” have familiarized us with the idea of com-puters that can speak and hear just as a human being does. Automatic speech recogni-tion (ASR) is the technol-ogy that allows machines to interpret human sp ...

2005

Improving Continuous Speech Recognition System Performance with Grapheme Modelling

Hervé Bourlard, Hynek Hermansky, John David Scott Dines

This paper investigates automatic speech recognition system using context-dependent graphemes as subword units based on the conventional HMM/GMM system as well as TANDEM system. Experimental studies conducted on two different continuous speech recognition ...

IDIAP2005

Short-Term Spatio-Temporal Clustering of Sporadic and Concurrent Events

Jean-Marc Odobez, Guillaume Lathoud

Accurate detection and segmentation of spontaneous multi-party speech is crucial for a variety of applications, including speech acquisition and recognition, as well as higher-level event recognition. However, the highly sporadic nature of spontaneous spee ...

IDIAP2004

Unsupervised Location-Based Segmentation of Multi-Party Speech

Jean-Marc Odobez, Guillaume Lathoud

2004

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

Stochastic resonance in pattern recognition by a holographic neuron model

Jonas Buchli

The recognition rate of holographic neural synapses, performing a pattern recognition task, is significantly higher when applied to natural, rather than artificial, images. This shortcoming of artificial images can be largely compensated for, if noise is a ...

2003

Offline Recognition of Large Vocabulary Cursive Handwritten Text

Samy Bengio, Alessandro Vinciarelli

This paper presents a system for the offline recognition of cursive handwritten lines of text. The system is based on continuous density HMMs and Statistical Language Models. The system recognizes data produced by a single writer. No a-priori knowledge is ...

IDIAP2003