[Association for Computational Linguistics the 33rd annual meeting - Cambridge, Massachusetts (1995.06.26-1995.06.30)] Proceedings of the 33rd annual meeting on Association for Computational Linguistics - - Bayesian grammar induction for language modeling

✍ Scribed by Chen, Stanley F.

• Book ID: 121837271
• Publisher: Association for Computational Linguistics
• Year: 1995
• Weight: 639 KB
• Category: Article
• DOI: 10.3115/981658.981689

✦ Synopsis

We describe a corpus-based induction algorithm for probabilistic context-free grammars. The algorithm employs a greedy heuristic search within a Bayesian framework, and a post-pass using the Inside-Outside algorithm. We compare the performance of our algorithm to n-gram models and the Inside-Outside algorithm in three language modeling tasks. In two of the tasks, the training data is generated by a probabilistic context-free grammar and in both tasks our algorithm outperforms the other techniques. The third task involves naturally-occurring data, and in this task our algorithm does not perform as well as n-gram models but vastly outperforms the Inside-Outside algorithm.