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A Spectrogram Model for Enhanced Source Localization and Noise-Robust ASR

Publications associées (34)

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Unsupervised Spectral Substraction for Noise-Robust ASR

Hervé Bourlard, Guillaume Lathoud, Bertrand Mesot

This paper proposes a simple, computationally efficient \mbox{2-mixture} model approach to discriminate between speech and background noise at the magnitude spectrogram level. It is directly derived from observations on real data, and can be used in a full ...

IDIAP2005

Unsupervised Spectral Subtraction for Noise-Robust ASR

Hervé Bourlard, Guillaume Lathoud, Bertrand Mesot

This paper proposes a simple, computationally efficient 2-mixture model approach to discriminate between speech and background noise at the magnitude spectrogram level. It is directly derived from observations on real data, and can be used in a fully unsup ...

2005

Continuous Microphone Array Speech Recognition on Wall Street Journal Corpus

Hervé Bourlard

In this paper, we present a robust speech acquisition system to acquire continuous speech using a microphone array. A microphone array based speech recognition system is also presented to study the environmental interference due to reverberation, backgroun ...

IDIAP2005

A Sector-Based Approach for Localization of Multiple Speakers with Microphone Arrays

Guillaume Lathoud

Microphone arrays are useful in meeting rooms, where speech needs to be acquired and segmented. For example, automatic speech segmentation allows enhanced browsing experience, and facilitates automatic analysis of large amounts of data. Spontaneous multi-p ...

IDIAP2004

A Sector-Based Approach for Localization of Multiple Speakers with Microphone Arrays

Guillaume Lathoud

2004

A Sector-Based, Frequency-Domain Approach to Detection and Localization of Multiple Speakers

Guillaume Lathoud

Detection and localization of speakers with microphone arrays is a difficult task due to the wideband nature of speech signals, the large amount of overlaps between speakers in spontaneous conversations, and the presence of noise sources. Many existing aud ...

IDIAP2004

Segmenting Multiple Concurrent Speakers Using Microphone Arrays

Guillaume Lathoud, Darren Moore

Speaker turn detection is an important task for many speech processing applications. However, accurate segmentation can be hard to achieve if there are multiple concurrent speakers (overlap), as is typically the case in multi-party conversations. In such c ...

IDIAP2003

Segmenting Multiple Concurrent Speakers Using Microphone Arrays

Guillaume Lathoud, Darren Moore

2003

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