Conditional Random Fields for Online Handwriting Recognition
Conditional Random Fields for Online Handwriting Recognition
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发表时间：
2006-10
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通讯作者：
T. Do;T. Artières
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作者：
T. Do;T. Artières
在这项工作中，我们提出了一个在线手写识别的条件模型。我们的方法是基于条件随机场（CRFs），这是一种概率判别模型，目前已被广泛用于特定设置中，用于标记和分析序列数据，如文本文档和生物序列。我们建议调整这些模型，以建立手写识别系统。我们提出了一些系统，其架构允许处理多模态类和利用片段特征，这些特征非常适合于在线手写等信号数据。
In this work, we present a conditional model for online handwriting recognition. Our approach is based on Conditional Random Fields (CRFs), a probabilistic discriminant model that has been generally used up to now in particular settings, for labeling and parsing of sequential data such as text documents and biological sequences. We propose to adapt these models in order to build systems for handwriting recognition. We propose a few systems whose architecture allows dealing with multimodal classes and exploiting segmental features that are much adapted to signal data like online handwriting.