Publications related to Microphone Array Beampattern Characterization for Hands-free Speech Applications

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 ...

2005

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

Multichannel Speech Enhancement in Cars: Explicit vs. Implicit Adaptation Control

Guillaume Lathoud

Speech-based command interfaces are becoming more and more common in cars. Applications include automatic dialog systems for hands-free phone calls as well as more advanced features such as navigation systems. However, interferences, such as speech from th ...

2005

Sector-Based Detection for Hands-Free Speech Enhancement in Cars

Guillaume Lathoud

Speech-based command interfaces are becoming more and more common in cars. Applications include automatic dialog systems for hands-free phone calls as well as more advanced features such as navigation systems. However, interferences, such as speech from th ...

IDIAP2004

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

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 ...

Ecole Polytechnique Federale de Lausanne2003

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 ...

IDIAP2003

Robust Speech Recognition with Small Microphone Arrays using the Missing Data Approach

Hervé Bourlard

Traditional microphone array speech recognition systems simply recognise the enhanced output of the array. As the level of signal enhancement depends on the number of microphones, such systems do not achieve acceptable speech recognition performance for ar ...

IDIAP2002

Robust Speech Recognition with Small Microphone Arrays using the Missing Data Approach

Hervé Bourlard

Traditional microphone array speech recognition systems simply recognise the enhanced output of the array. As the level of signal enhancement depends on the number of microphones, such systems do not achieve acceptable speech recognition performance for ar ...

2002

Automatic Speech Recognition using Pitch Information in Dynamic Bayesian Networks

Hervé Bourlard

The challenge of automatic speech recognition (ASR) increases when speaker variability is encountered. Being able to automatically use different acoustic models according to speaker type might help to increase the robustness of ASR. We present a system tha ...

IDIAP2000

Microphone Array Beampattern Characterization for Hands-free Speech Applications

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Speech Acquisition in Meetings with an Audio-Visual Sensor Array

Using Pitch as Prior Knowledge in Template-Based Speech Recognition

Multichannel Speech Enhancement in Cars: Explicit vs. Implicit Adaptation Control

Sector-Based Detection for Hands-Free Speech Enhancement in Cars

HMM mixtures (HMM2) for robust speech recognition

HMM Mixtures (HMM2) for Robust Speech Recognition

HMM Mixtures (HMM2) for Robust Speech Recognition

Robust Speech Recognition with Small Microphone Arrays using the Missing Data Approach

Robust Speech Recognition with Small Microphone Arrays using the Missing Data Approach

Automatic Speech Recognition using Pitch Information in Dynamic Bayesian Networks

Speech Acquisition in Meetings with an Audio-Visual Sensor Array

Sector-Based Detection for Hands-Free Speech Enhancement in Cars

Using Pitch as Prior Knowledge in Template-Based Speech Recognition

Multichannel Speech Enhancement in Cars: Explicit vs. Implicit Adaptation Control

HMM mixtures (HMM2) for robust speech recognition

HMM Mixtures (HMM2) for Robust Speech Recognition

HMM Mixtures (HMM2) for Robust Speech Recognition

Robust Speech Recognition with Small Microphone Arrays using the Missing Data Approach

Robust Speech Recognition with Small Microphone Arrays using the Missing Data Approach

Automatic Speech Recognition using Pitch Information in Dynamic Bayesian Networks