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NYU Language Modeling Experiments for the 1996 CSR Evaluation

机译：用于1996年CSR评估的NYU语言建模实验

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摘要

This paper describes NYU's effort toward improving recognition accuracy for the 1996 ARPA Large Vocabulary Continuous Speech Recognition evaluation. We are trying to develop different kinds of language models including longer-range models and a linguistically motivated model. For the system described here, we used as a starting point the scores produced by SRI's acoustic and language models. These are linearly combined with the scores produced by the NYU language models. This paper also describes some experiments we tried which were not used in the official experiment, including experiments with perplexity minimization, Maximum Entropy modeling and parsing.
机译：本文介绍了纽约大学为提高1996 ARPA大词汇量连续语音识别评估的识别准确性所做的努力。我们正在尝试开发不同种类的语言模型，包括远程模型和语言动机模型。对于此处描述的系统，我们以SRI的声学和语言模型产生的分数作为起点。这些与NYU语言模型产生的分数线性组合。本文还介绍了我们尝试过的一些未在正式实验中使用过的实验，包括最小化困惑度，最大熵建模和解析的实验。

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