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ACL
2003

Generalized Algorithms for Constructing Statistical Language Models

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Generalized Algorithms for Constructing Statistical Language Models
Recent text and speech processing applications such as speech mining raise new and more general problems related to the construction of language models. We present and describe in detail several new and efficient algorithms to address these more general problems and report experimental results demonstrating their usefulness. We give an algorithm for computing efficiently the expected counts of any sequence in a word lattice output by a speech recognizer or any arbitrary weighted automaton; describe a new technique for creating exact representations of ¢ -gram language models by weighted automata whose size is practical for offline use even for a vocabulary size of about 500,000 words and an ¢ -gram order ¢¤£¦¥ ; and present a simple and more general technique for constructing class-based language models that allows each class to represent an arbitrary weighted automaton. An efficient implementation of our algorithms and techniques has been incorporated in a general software...
Cyril Allauzen, Mehryar Mohri, Brian Roark
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2003
Where ACL
Authors Cyril Allauzen, Mehryar Mohri, Brian Roark
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