ACL RD-TEC 1.0 Summarization of W03-1703

Paper Title:
UTTERANCE SEGMENTATION USING COMBINED APPROACH BASED ON BI-DIRECTIONAL N-GRAM AND MAXIMUM ENTROPY

Authors: Ding Liu and Chengqing Zong

Other assigned terms:

  • ambiguity
  • approach
  • beam
  • brown corpus
  • case
  • characters
  • chinese characters
  • conditional probability
  • corpora
  • dialogues
  • dictionary
  • discourse
  • distribution
  • entropy
  • experimental results
  • feature
  • intention
  • joint probability
  • joint probability distribution
  • language model
  • language models
  • lexical context
  • lexical information
  • likelihood
  • linguistic
  • linguistic model
  • markov chain
  • maximum-entropy-based model
  • method
  • n-gram
  • n-gram language model
  • n-gram model
  • n-gram models
  • n-grams
  • natural language
  • natural language user
  • part of speech
  • part-of-speech
  • part-of-speech information
  • pauses
  • precision
  • probabilities
  • probability
  • probability distribution
  • punctuation
  • punctuation marks
  • recognition model
  • segmentation accuracy
  • segments
  • semantic
  • sentence
  • sentence boundaries
  • sentence boundary
  • sentences
  • speech information
  • spoken language
  • suffix
  • suffixes
  • symbols
  • tags
  • test corpora
  • test corpus
  • test set
  • text
  • training
  • training corpora
  • training corpus
  • training data
  • transcripts
  • trees
  • trigram
  • understanding
  • user
  • user utterances
  • utterance
  • word
  • word sequence
  • word sequences
  • words

Extracted Section Types:


This page last edited on 10 May 2017.

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