NLP应用的置信度估计

ACM Trans. Speech Lang. Process. Pub Date : 2006-10-01 DOI:10.1145/1177055.1177057

Simona Gandrabur, George F. Foster, G. Lapalme

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引用次数: 45

摘要

置信度度量是提高自然语言处理应用的实用性的一种实际解决方案。置信度估计是一种用于获得置信度度量的通用机器学习方法。我们概述了置信度估计在自然语言处理各个领域的应用，并给出了在语音识别、口语理解和统计机器翻译方面的实验结果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Confidence estimation for NLP applications

Confidence measures are a practical solution for improving the usefulness of Natural Language Processing applications. Confidence estimation is a generic machine learning approach for deriving confidence measures. We give an overview of the application of confidence estimation in various fields of Natural Language Processing, and present experimental results for speech recognition, spoken language understanding, and statistical machine translation.

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来源期刊

ACM Trans. Speech Lang. Process.

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