A Cache-Based Natural Language Model for Speech Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
HLT '89 Proceedings of the workshop on Speech and Natural Language
Statistical parsing of messages
HLT '90 Proceedings of the workshop on Speech and Natural Language
A stochastic parts program and noun phrase parser for unrestricted text
ANLC '88 Proceedings of the second conference on Applied natural language processing
A tool for investigating the synonymy relation in a sense disambiguated thesaurus
ANLC '88 Proceedings of the second conference on Applied natural language processing
Dictionaries, dictionary grammars and dictionary entry parsing
ACL '89 Proceedings of the 27th annual meeting on Association for Computational Linguistics
ACL '90 Proceedings of the 28th annual meeting on Association for Computational Linguistics
Unification-based semantic interpretation in the BBN Spoken Language System
HLT '89 Proceedings of the workshop on Speech and Natural Language
Parsing, word associations and typical predicate-argument relations
HLT '89 Proceedings of the workshop on Speech and Natural Language
Partial parsing: a report on work in progress
HLT '91 Proceedings of the workshop on Speech and Natural Language
Parsing the voyager domain using pearl
HLT '91 Proceedings of the workshop on Speech and Natural Language
Studies in part of speech labelling
HLT '91 Proceedings of the workshop on Speech and Natural Language
Communications of the ACM
Introduction to the special issue on computational linguistics using large corpora
Computational Linguistics - Special issue on using large corpora: I
Pearl: a probabilistic chart parser
EACL '91 Proceedings of the fifth conference on European chapter of the Association for Computational Linguistics
BBN: description of the PLUM system as used for MUC-3
MUC3 '91 Proceedings of the 3rd conference on Message understanding
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In order to meet the information processing demands of the next decade, natural language systems must have the capability of processing very large amounts of text, commonly called "messages", from highly diverse sources written in any of a few dozen languages. One of the key issues in building systems with this scale of competence is handling large numbers of different words and word senses. Natural language understanding systems today are typically limited to vocabularies of less than 10,000 words; tomorrow's systems will need vocabularies at least 5 times that to effectively handle the volume and diversity of messages needing to be processed.