Language processing for speech understanding
Computer speech processing
A Cache-Based Natural Language Model for Speech Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Integrating speech and natural-language processing
HLT '89 Proceedings of the workshop on Speech and Natural Language
Probabilistic Languages: A Review and Some Open Questions
ACM Computing Surveys (CSUR)
Introduction to Formal Language Theory
Introduction to Formal Language Theory
The Design and Analysis of Computer Algorithms
The Design and Analysis of Computer Algorithms
The Theory of Parsing, Translation, and Compiling
The Theory of Parsing, Translation, and Compiling
Optimal Probabilistic Evaluation Functions for Search Controlled by Stochastic Context-Free Grammars
IEEE Transactions on Pattern Analysis and Machine Intelligence
An efficient probabilistic context-free parsing algorithm that computes prefix probabilities
Computational Linguistics
Program representation and behavioural matching for localizing similar code fragments
CASCON '93 Proceedings of the 1993 conference of the Centre for Advanced Studies on Collaborative research: software engineering - Volume 1
The development of a partial design recovery environment for legacy systems
CASCON '93 Proceedings of the 1993 conference of the Centre for Advanced Studies on Collaborative research: software engineering - Volume 1
Precise n-gram probabilities from stochastic context-free grammars
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Probabilistic Context-Free Grammars Estimated from Infinite Distributions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computation of distances for regular and context-free probabilistic languages
Theoretical Computer Science
Computation of upper-bounds for stochastic context-free languages
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
Prefix probability for probabilistic synchronous context-free grammars
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Computation of infix probabilities for probabilistic context-free grammars
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Prefix probabilities for linear context-free rewriting systems
IWPT '11 Proceedings of the 12th International Conference on Parsing Technologies
Stochastic context-free grammars, regular languages, and newton's method
ICALP'13 Proceedings of the 40th international conference on Automata, Languages, and Programming - Volume Part II
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The authors describe an effort to adapt island-driven parsers to handle stochastic context-free grammars. These grammars could be used as language models (LMs) by a language processor (LP) to computer the probability of a linguistic interpretation. As different islands may compete for growth, it is important to compute the probability that an LM generates a sentence containing islands and gaps between them. Algorithms for computing these probabilities are introduced. The complexity of these algorithms is analyzed both from theoretical and practical points of view. It is shown that the computation of probabilities in the presence of gaps of unknown length requires the impractical solution of a nonlinear system of equations, whereas the computation of probabilities for cases with gaps containing a known number of unknown words has polynomial time complexity and is practically feasible. The use of the results obtained in automatic speech understanding systems is discussed.