This paper revisits the work of (Malladi and Mannem, 2013) which focused on building a Statistical Morphological Analyzer (SMA) for Hindi and compares the performance of SMA with other existing statistical analyzer, Morfette. We shall evaluate SMA in various experiment scenarios and look at how it performs for unseen words. The later part of the paper presents the effect of the predicted morph features on dependency parsing and extends the work to other morphologically rich languages: Hindi and Telugu, without any language-specific engineering.
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机译：本文回顾了（Malladi and Mannem，2013）的工作，该工作重点是为北印度语构建统计形态分析仪（SMA），并将SMA的性能与其他现有统计分析仪Morfette进行了比较。我们将在各种实验场景中评估SMA，并研究其在看不见的单词中的表现。本文的后半部分介绍了预测的词素特征对依赖项解析的影响，并将工作扩展到其他形态丰富的语言：北印度语和泰卢固语，而无需进行任何语言特定的工程设计。
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