第二个“CHiME”语音分离和识别挑战:挑战系统和结果概述

Emmanuel Vincent, Jon Barker, Shinji Watanabe, Jonathan Le Roux, Francesco Nesta, Marco Matassoni
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引用次数: 94

摘要

在涉及多背景源和混响的日常环境中,远距离麦克风自动语音识别(ASR)仍然是一个具有挑战性的目标。本文报告了第二次“CHiME”挑战的结果,这是一项旨在分析和评估ASR系统在真实家庭环境中的性能的倡议。我们讨论了挑战的基本原理,并提供了数据集、任务和基线系统的摘要。本文概述了两个挑战轨道的系统:移动说话者的小词汇量和静止说话者的中等词汇量。我们提出了挑战结果的总结,包括挑战系统组合产生的新结果。讨论了未来挑战的可能方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The second ‘CHiME’ speech separation and recognition challenge: An overview of challenge systems and outcomes
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 rationale for the challenge and provide a summary of the datasets, tasks and baseline systems. The paper overviews the systems that were entered for the two challenge tracks: small-vocabulary with moving talker and medium-vocabulary with stationary talker. We present a summary of the challenge findings including novel results produced by challenge system combination. Possible directions for future challenges are discussed.
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