A stochastically based approach for the semantic analysis component of a natural spoken language system for the ARPA Air Travel Information Services (ATIS) task has been developed. The semantic analyzer of the spoken language system already in use at LIMSI makes use of a rule-based case grammar. In this work, the system of rules for the semantic analysis is replaced with a relatively simple first-order hidden Markov model. The performances of the two approaches can be compared because they use identical semantic representations, despite their rather different methods for meaning extraction. We use an evaluation methodology that assesses performance at different semantic levels, including the database response comparison used in the ARPA ATIS paradigm.
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机译：已经开发出一种基于基于基于基于ARPA Air Travel信息服务（ATIS）任务的语义分析组件的方法。 LiMSI已经使用的口语系统的语义分析仪利用基于规则的案例语法。在这项工作中，用一个相对简单的一阶隐马尔可夫模型替换了语义分析规则系统。尽管它们相当不同的含义提取方法，但可以比较两种方法的性能，因为它们使用相同的语义表示。我们使用评估方法，评估不同语义级别的性能，包括ARPA ATIS范例中使用的数据库响应比较。
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