作者: H. Rulot , E. Vidal
DOI: 10.1007/978-3-642-83462-2_11
关键词: Parsing 、 Concatenation 、 Computer science 、 Grammar induction 、 Attribute grammar 、 Regular grammar 、 Adaptive neuro fuzzy inference system 、 Inference 、 Automata theory 、 Theoretical computer science
摘要: In this paper, a recently introduced grammatical inference method is reviewed. method, non left(right)-recursive regular grammar built in an incremental way: as each training sample presented, it parsed by the current (error-correcting extended) grammar, minimizing explicitly, dynamic programming, number of error-rules needed. These are then added to grammar. This procedure has proved be well suited for capturing relevant information associated with lengths substructures patterns analized, and their concatenation. A stochastic extension some alternative approaches estimating probabilities both error non-error rules discussed. Finally, results experiments speech samples, which show capabilities proposed summarized.