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Interactive Pattern Recognition

机译:互动模式识别

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摘要

Pattern Recognition systems are not error-free. Human intervention is typically needed to verify and/or correct the result of such systems. To formalize this fact, a new framework, which integrates the human activity into the recognition process taking advantage of the user's feedback, is described. Several applications, involving Interactive Speech Transcription and Multimodal Interactive Machine Translation, have recently been considered under this framework. These applications are reviewed in this paper, and some experiments, showing that the proposed framework can save significant amounts of human effort, are also presented.
机译:模式识别系统不是无差错的。人类干预通常需要验证和/或校正这些系统的结果。为了形式化这一事实,描述了一种新的框架,将人类活动集成到利用用户反馈的识别过程中。在此框架下,最近考虑了几种涉及互动语音转录和多模式交互式机器翻译的应用程序。本文审查了这些应用,并显示了拟议的框架可以节省大量人力努力的实验。

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