Learn More
Distant-microphone automatic speech recognition (ASR) remains a challenging goal in everyday environments involving multiple background sources and reverberation. This paper is intended to be a reference on the 2nd 'CHiME' Challenge, an initiative designed to analyze and evaluate the performance of ASR systems in a real-world domestic environment. Two(More)
This paper describes the system used to process the data of the CHiME Pascal 2011 competition, whose goal is to separate the desired speech and recognize the commands being spoken. The binaural recorded mixtures are processed by an on-line Semi-Blind Source Extraction algorithm. The algorithm is based on a multi-stage architecture combining the advantages(More)
This paper summarizes the audio part of the 2011 community-based Signal Separation Evaluation Campaign (SiSEC2011). Four speech and music datasets were contributed, including datasets recorded in noisy or dynamic environments and a subset of the SiSEC2010 datasets. The participants addressed one or more tasks out of four source separation tasks, and the(More)
Blind source extraction (BSE) is an attractive approach to enhance multichannel noisy speech data, as a preprocessing step for an automatic speech recognition system. BSE was successfully applied to the first Chime Pascal Challenge for improving the recognition rate of noisy commands in a small dictionary task. In this work we reviewed the BSE architecture(More)
This paper presents a general framework for tracking the time differences of arrivals of multiple acoustic sources recorded by distributed microphone pairs. Tracking is based on a three-stage analysis. Complex-valued propagation models are extracted at different time instants and frequencies using either the independent component analysis or the phase of(More)
—This paper proposes a new method of Frequency-Domain Blind Source Separation (FD-BSS), able to separate acoustic sources in challenging conditions. In frequency-domain BSS, the time-domain signals are transformed in time-frequency series and the separation is generally performed by applying the Independent Component Analysis (ICA) at each frequency(More)
Distant-microphone automatic speech recognition (ASR) remains a challenging goal in everyday environments involving multiple background sources and reverberation. This paper reports on the results of the 2nd 'CHiME' Challenge, an initiative designed to analyse and evaluate the performance of ASR systems in a real-world domestic environment. We discuss the(More)
This paper presents a novel method for underdetermined acoustic source separation of convolutive mixtures. Multiple complex-valued Independent Component Analysis adaptations jointly estimate the mixing matrix and the temporal activities of multiple sources in each frequency. A structure based on a recursive temporal weighting of the gradient enforces each(More)