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arXiv · 1803.10609

The fifth 'CHiME' Speech Separation and Recognition Challenge: Dataset, task and baselines

Jon Barker·Shinji Watanabe·Emmanuel Vincent·Jan Trmal
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Abstract

The CHiME challenge series aims to advance robust automatic speech recognition (ASR) technology by promoting research at the interface of speech and language processing, signal processing , and machine learning. This paper introduces the 5th CHiME Challenge, which considers the task of distant multi-microphone conversational ASR in real home environments. Speech material was elicited using a dinner party scenario with efforts taken to capture data that is representative of natural conversational speech and recorded by 6 Kinect microphone arrays and 4 binaural microphone pairs. The challenge features a single-array track and a multiple-array track and, for each track, distinct rankings will be produced for systems focusing on robustness with respect to distant-microphone capture vs. systems attempting to address all aspects of the task including conversational language modeling. We discuss the rationale for the challenge and provide a detailed description of the data collection procedure, the task, and the baseline systems for array synchronization, speech enhancement, and conventional and end-to-end ASR.

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Jon Barker, Shinji Watanabe, Emmanuel Vincent, Jan Trmal. 2018-03-28. The fifth 'CHiME' Speech Separation and Recognition Challenge: Dataset, task and baselines. https://arxiv.org/abs/1803.10609

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