ACL RD-TEC 1.0 Summarization of H94-1015

Paper Title:
SPEECH RECOGNITION USING A STOCHASTIC LANGUAGE MODEL INTEGRATING LOCAL AND GLOBAL CONSTRAINTS

Authors: Ryosuke Isotani and Shoichi Matsunaga

Other assigned terms:

  • acoustic score
  • approach
  • auxiliary verb
  • auxiliary verbs
  • beam
  • bigram
  • bigram model
  • bunsetsu
  • case
  • case information
  • content words
  • continuous speech
  • corpora
  • distribution
  • estimation
  • fact
  • function word
  • function words
  • hypotheses
  • interpolation
  • japanese sentences
  • japanese text
  • knowledge
  • language model
  • language models
  • lattices
  • likelihood
  • linear combination
  • linguistic
  • linguistic constraints
  • linguistic knowledge
  • local constraints
  • long distance dependencies
  • markov models
  • measure
  • method
  • model parameters
  • mutual information
  • n-gram
  • n-gram model
  • n-gram models
  • n-grams
  • nouns
  • part of speech
  • part of speech tags
  • particles
  • parts of speech
  • perplexity
  • phrase
  • probabilities
  • probability
  • probability value
  • process
  • pronunciation
  • recognition accuracy
  • recognition rate
  • recognition task
  • semantic
  • semantic constraints
  • semantic information
  • semantic relationships
  • sentence
  • sentences
  • speech data
  • speech recognition accuracy
  • statistical measure
  • statistics
  • stochastic language model
  • substring
  • symbols
  • syntactic and semantic information
  • syntactic constraints
  • tags
  • telecommunications research
  • term
  • test data
  • text
  • text corpora
  • text database
  • training
  • training and test data
  • training data
  • tree
  • trigram
  • trigram model
  • uniform distribution
  • verb
  • vocabulary
  • vocabulary size
  • word
  • word bigram model
  • word pair
  • word sequence
  • word sequences
  • word string
  • word trigram
  • word trigram model
  • words

Extracted Section Types:


This page last edited on 10 May 2017.

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