The ATIS spoken language systems pilot corpus
HLT '90 Proceedings of the workshop on Speech and Natural Language
Smooth on-line learning algorithms for hidden Markov models
Neural Computation
Class-Based Construction of a Verb Lexicon
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Automatic grammar generation from two different perspectives
Automatic grammar generation from two different perspectives
Towards efficient statistical parsing using lexicalized grammatical information
Towards efficient statistical parsing using lexicalized grammatical information
Building a large annotated corpus of English: the penn treebank
Computational Linguistics - Special issue on using large corpora: II
Supertagging: an approach to almost parsing
Computational Linguistics
New models for improving supertag disambiguation
EACL '99 Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics
LiLFeS: towards a practical HPSG parser
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Integrating compositional semantics into a verb lexicon
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Extraction of tree adjoining grammars from a treebank for Korean
COLING ACL '06 Proceedings of the 21st International Conference on computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop
MICA: a probabilistic dependency parser based on tree insertion grammars application note
NAACL-Short '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers
Journal of Computer and System Sciences
Bridge the gap between statistical and hand-crafted grammars
Computer Speech and Language
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Though the lack of semantic representation of automatically extracted LTAGs is an obstacle in using these formalism, due to the advent of some powerful statistical parsers that were trained on them, these grammars have been taken into consideration more than before. Against of this grammatical class, there are some widely usage manually crafted LTAGs that are enriched with semantic representation but suffer from the lack of efficient parsers. The available representation of latter grammars beside the statistical capabilities of former encouraged us in constructing a link between them. Here, by focusing on the automatically extracted LTAG used by MICA [4] and the manually crafted English LTAG namely XTAG grammar [32], a statistical approach based on HMM is proposed that maps each sequence of former elementary trees onto a sequence of later elementary trees. To avoid of converging the HMM training algorithm in a local optimum state, an EM-based learning process for initializing the HMM parameters were proposed too. Experimental results show that the mapping method can provide a satisfactory way to cover the deficiencies arises in one grammar by the available capabilities of the other.