Marc Delcroix

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Recently, substantial progress has been made in the field of reverberant speech signal processing, including both single- and multichannel dereverberation techniques, and automatic speech recognition (ASR) techniques robust to reverberation. To evaluate state-of-the-art algorithms and obtain new insights regarding potential future research directions, we(More)
Inverse filtering of room transfer functions (RTFs) is considered an attractive approach for speech dereverberation given that the time invariance assumption of the used RTFs holds. However, in a realistic environment, this assumption is not necessarily guaranteed, and the performance is degraded because the RTFs fluctuate over time and the inverse filter(More)
A speech signal captured by a distant microphone is generally smeared by reverberation, which severely degrades automatic speech recognition (ASR) performance. One way to solve this problem is to dereverberate the observed signal prior to ASR. In this paper, a room impulse response is assumed to consist of three parts: a direct-path response, early(More)
Speech recognition technology has left the research laboratory and is increasingly coming into practical use, enabling a wide spectrum of innovative and exciting voice-driven applications that are radically changing our way of accessing digital services and information. Most of today's applications still require a microphone located near the talker.(More)
In this paper, we discuss the numerical problems posed by the previously reported LInear-predictive Multi-input Equalization (LIME) algorithm when dealing with dereverberation of long room transfer functions (RTF). The LIME algorithm consists of two steps. First, a speech residual is calculated using multichannel linear prediction. The residual is free from(More)
In this paper, we introduce a system for recognizing speech in the presence of multiple rapidly time-varying noise sources. The main components of the proposed approach are a modelbased speech enhancement pre-processor and an adaptation technique to optimize the integration between the pre-processor and the recognizer. The speech enhancement pre-processor(More)
This paper describes systems for the enhancement and recognition of distant speech recorded in reverberant rooms. Our speech enhancement (SE) system handles reverberation with blind deconvolution using linear filtering estimated by exploiting the temporal correlation of observed reverberant speech signals. Additional noise reduction is then performed using(More)
The performance of automatic speech recognition is severely degraded in the presence of noise or reverberation. Much research has been undertaken on noise robustness. In contrast, the problem of the recognition of reverberant speech has received far less attention and remains very challenging. In this paper, we use a dereverberation method to reduce(More)
In recent years, substantial progress has been made in the field of reverberant speech signal processing, including both singleand multichannel dereverberation techniques and automatic speech recognition (ASR) techniques that are robust to reverberation. In this paper, we describe the REVERB challenge, which is an evaluation campaign that was designed to(More)