Flexible Noisy Text Correction

Andrey C. Sariev, Vladislav Nenchev, Stefan Gerdjikov, Petar Mitankin, Hristo Ganchev, S. Mihov, Tinko Tinchev
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引用次数: 6

Abstract

We present a new general and language independent approach to the noisy text correction problem developed and implemented in the framework of the CULTURA project. We briefly describe the core candidate generator, REBELS, the complete system concept, its efficient implementation based on functional automata and its immediate applications. The quality of the whole system is empirically established in different experimental settings where language and noise sources are varied.
灵活的噪声文本校正
我们提出了一种新的通用和语言独立的方法来解决在CULTURA项目框架内开发和实施的噪声文本校正问题。简要介绍了核心候选生成器——REBELS、完整的系统概念、基于函数自动机的有效实现及其直接应用。整个系统的质量是在不同的实验环境中经验建立的,其中语言和噪声源是不同的。
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