We present a parametric model-based multichannel approach for speech enhancement. By employing an autoregressive model for the speech signal and using a trained codebook of speech linear predictive coefficients, minimum mean square error estimation of the speech signal is performed. By explicitly accounting for steering errors in the signal model, robust estimates are obtained. Experiments show that the proposed method results in significant performance gains
In this paper, we propose a Bayesian minimum mean squared error approach for the joint estimation of...
Speech recognition has been used in various real-world applications such as automotive control, elec...
The paper describes a system for automatic speech recognition (ASR) that is benchmarked with data of...
We present a parametric model-based multichannel approach for speech enhancement. By employing an au...
The goal of speech enhancement is to reduce the noise signal while keeping the speech signal undisto...
The goal of this work is to generalize speech enhancement methods from single channel microphones, d...
In this study, the authors propose multichannel weighted Euclidean (WE) and weighted cosh (WCOSH) co...
In this paper, the authors present optimal multichannel frequency domain estimators for minimum mean...
This article introduces an extension of the improved minima-controlled recursive averaging noise est...
The use of microphone arrays in speech enhancement applications offer additional features, like dire...
Speech is a fundamental means of human communication. In the last several decades, much effort has b...
In this paper, a method for multi-channel pitch estimation is proposed. The method is a maximum like...
International audienceWe propose a semi-supervised multichannel speech enhancement system based on a...
Compared with single-channel speech enhancement methods, multichannel methods can utilize spatial in...
International audienceThis paper introduces a new method for multichannel speech enhancement based o...
In this paper, we propose a Bayesian minimum mean squared error approach for the joint estimation of...
Speech recognition has been used in various real-world applications such as automotive control, elec...
The paper describes a system for automatic speech recognition (ASR) that is benchmarked with data of...
We present a parametric model-based multichannel approach for speech enhancement. By employing an au...
The goal of speech enhancement is to reduce the noise signal while keeping the speech signal undisto...
The goal of this work is to generalize speech enhancement methods from single channel microphones, d...
In this study, the authors propose multichannel weighted Euclidean (WE) and weighted cosh (WCOSH) co...
In this paper, the authors present optimal multichannel frequency domain estimators for minimum mean...
This article introduces an extension of the improved minima-controlled recursive averaging noise est...
The use of microphone arrays in speech enhancement applications offer additional features, like dire...
Speech is a fundamental means of human communication. In the last several decades, much effort has b...
In this paper, a method for multi-channel pitch estimation is proposed. The method is a maximum like...
International audienceWe propose a semi-supervised multichannel speech enhancement system based on a...
Compared with single-channel speech enhancement methods, multichannel methods can utilize spatial in...
International audienceThis paper introduces a new method for multichannel speech enhancement based o...
In this paper, we propose a Bayesian minimum mean squared error approach for the joint estimation of...
Speech recognition has been used in various real-world applications such as automotive control, elec...
The paper describes a system for automatic speech recognition (ASR) that is benchmarked with data of...