用于手写识别的统一法语/英语音节模型

Wassim Swaileh, Julien Lerouge, T. Paquet
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引用次数: 2

摘要

本文提出了一种新的基于隐马尔可夫模型(HMM)的法语和英语手写识别统一音节模型。识别系统的训练和识别组件如光学模型、词汇和语言模型被设计成与语言无关。为此,我们提出了一种基于音节的法语和英语模型。该模型被评估并与n-gram字符和单词模型进行比较。音节模型达到了单词模型的性能要求,具有降低系统复杂度的优点。此外,考虑到英语和法语,可能相似脚本的统一提高了所有模型的系统性能。法国RIMES和英国IAM数据集用于评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Unified French/English Syllabic Model for Handwriting Recognition
In this paper we introduce a new unified syllabic model for French and English handwriting recognition, based on hidden Markov models (HMM). The recognition system training and recognition components such as optical models, lexicons and language models are designed to be language independent. In this purpose a syllable based model is proposed for French and English. This model is evaluated and compared to n-gram character and words models. A promising performance is achieved by the syllabic model, which meets the words model performance, with the advantage of a reduced system complexity. Furthermore, the unification of likely similar scripts improves the system performance over all models considering the English and French languages. The French RIMES and the English IAM datasets are used for the evaluation.
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