ACL RD-TEC 1.0 Summarization of P05-1042

Paper Title:
A DYNAMIC BAYESIAN FRAMEWORK TO MODEL CONTEXT AND MEMORY IN EDIT DISTANCE LEARNING: AN APPLICATION TO PRONUNCIATION CLASSIFICATION

Authors: Karim Filali and Jeff Bilmes

Other assigned terms:

  • alphabet
  • annotation
  • automata
  • backoff
  • bayesian framework
  • biology
  • case
  • chunk
  • classification rule
  • classification task
  • computational complexity
  • conditional probabilities
  • conditional probability
  • context models
  • dependency structures
  • dictionary
  • distribution
  • edit distance
  • empty string
  • error rate
  • events
  • fact
  • feature
  • frame
  • generative model
  • graph edit distance
  • implementation
  • index
  • interpolation
  • joint probability
  • levenshtein distance
  • levenshtein edit distance
  • lexicon
  • likelihood
  • logic
  • mapping
  • maps
  • measure
  • method
  • model context
  • model parameters
  • natural language
  • network structure
  • noise
  • phoneme
  • probabilities
  • probability
  • probability distribution
  • procedure
  • process
  • pronunciation
  • pronunciation dictionary
  • recognition evaluation
  • recursion
  • running time
  • segments
  • statistics
  • stochastic model
  • string edit distance
  • subgraph
  • substring
  • surface form
  • symbol
  • symbols
  • target string
  • terms
  • test set
  • training
  • training data
  • transformation
  • transposition
  • word
  • word model
  • word sequence
  • words

Extracted Section Types:


This page last edited on 10 May 2017.

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