ACL RD-TEC 1.0 Summarization of J92-4003

Paper Title:
CLASS-BASED N-GRAM MODELS OF NATURAL LANGUAGE

Authors: Peter F. Brown and Peter V. deSouza and Robert L. Mercer and T. J. Watson and Vincent J. Della Pietra and Jenifer C. Lai

Other assigned terms:

  • 1-gram word distribution
  • acoustic signal
  • approach
  • binary tree
  • brown corpus
  • case
  • characters
  • cluster
  • clusters
  • co-occurrence
  • co-occurrence statistics
  • coherence
  • concept
  • concepts
  • conditional probabilities
  • conditional probability
  • distribution
  • english text
  • entropy
  • estimation
  • fact
  • implementation
  • joint probability
  • language model
  • language models
  • language processing tasks
  • likelihood
  • linguistics
  • mapping
  • maps
  • maximum likelihood estimate
  • meaning
  • measure
  • method
  • mutual information
  • n-gram
  • n-gram language model
  • n-gram model
  • n-gram models
  • n-grams
  • names
  • natural language
  • natural language processing tasks
  • noisy channel
  • pairs of words
  • passage
  • perplexity
  • posteriori probability
  • precision
  • priori
  • probabilities
  • probability
  • probability distribution
  • process
  • processing tasks
  • proper names
  • relative frequency
  • semantic
  • semantic classes
  • semantic coherence
  • signal
  • statistics
  • stem
  • stems
  • syntactic function
  • technique
  • term
  • terms
  • test data
  • text
  • theory
  • training
  • training data
  • training text
  • transition matrix
  • tree
  • vocabulary
  • word
  • word classes
  • word distribution
  • word strings
  • word-based language model
  • word-based model
  • words

Extracted Section Types:


This page last edited on 10 May 2017.

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