ACL RD-TEC 1.0 Summarization of W06-1624

Paper Title:
A WEAKLY SUPERVISED LEARNING APPROACH FOR SPOKEN LANGUAGE UNDERSTANDING

Authors: Wei-Lin Wu and Ru-Zhan Lu and Jian-Yong Duan and Hui Liu and Feng Gao and Yu-Quan Chen

Other assigned terms:

  • anchors
  • annotated corpus
  • annotation
  • approach
  • association for computational linguistics
  • binary features
  • case
  • character error rate
  • characters
  • chinese characters
  • class probability
  • classification performance
  • classification problem
  • collocation
  • complex word
  • concept
  • concepts
  • confidence score
  • confidence scores
  • context feature
  • context features
  • data set
  • data sparseness
  • data sparseness problem
  • dialog
  • dialog context
  • dialogues
  • domain model
  • error rate
  • experimental results
  • fact
  • feature
  • feature vector
  • frame
  • grammar
  • hierarchical structure
  • labeled training data
  • labeling
  • language corpus
  • lexical rules
  • lexical semantic
  • lexicon
  • linguistic
  • linguistics
  • measure
  • method
  • n-gram
  • named entities
  • namedentity
  • names
  • natural language
  • noise
  • pauses
  • preprocessor
  • probability
  • procedure
  • process
  • queries
  • query
  • search space
  • seed
  • semantic
  • semantic class
  • semantic frame
  • semantic grammar
  • semantic lexicon
  • semantic representation
  • sentence
  • sentences
  • slot
  • sparseness problem
  • spoken language
  • spoken language corpus
  • support vector
  • svms
  • system architecture
  • system performance
  • technique
  • terms
  • test set
  • text
  • toolkit
  • topics
  • training
  • training data
  • training examples
  • training set
  • tree
  • uncertainty-based strategy
  • understanding
  • unlabeled examples
  • user
  • utterance
  • word
  • word sequence
  • word sequences
  • words

Extracted Section Types:


This page last edited on 10 May 2017.

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