ACL RD-TEC 1.0 Summarization of P06-2025

Paper Title:
A MODIFIED JOINT SOURCE-CHANNEL MODEL FOR TRANSLITERATION

Authors: Asif Ekbal and Sudip Kumar Naskar and Sivaji Bandyopadhyay

Other assigned terms:

  • alphabet
  • approach
  • association for computational linguistics
  • back-transliteration
  • bigram
  • bigram model
  • bilingual dictionaries
  • bilingual dictionary
  • bilingual training corpus
  • characters
  • collocation
  • conjunct
  • context information
  • contextual information
  • dictionaries
  • dictionary
  • entropy
  • evaluation metrics
  • feature
  • foreign words
  • heuristic
  • hypothesis
  • joint probability
  • katakana
  • knowledge
  • knowledge base
  • likelihood
  • linguistic
  • linguistic features
  • linguistic information
  • linguistic knowledge
  • linguistic knowledge base
  • linguistics
  • literal translation
  • many-to-one relationship
  • mapping
  • mappings
  • maps
  • method
  • modifier
  • n-gram
  • n-gram transliteration model
  • named entities
  • named entity
  • names
  • natural language
  • nlp applications
  • open test
  • person names
  • personal names
  • probabilistic model
  • probability
  • probability model
  • procedure
  • process
  • pronunciation
  • pronunciation dictionary
  • regular expressions
  • representations
  • segments
  • sense disambiguation problem
  • source channel model
  • source language
  • source-channel model
  • statistical model
  • statistics
  • syllables
  • symbols
  • target language
  • target languages
  • technical terms
  • technique
  • temporal expressions
  • terms
  • test corpus
  • test set
  • training
  • training corpus
  • training examples
  • training phase
  • training set
  • transformation
  • transformation rules
  • translation model
  • transliteration model
  • trigram
  • trigram model
  • unigram
  • unit agreement ratio
  • user
  • vocabulary
  • vowel
  • word
  • words

Extracted Section Types:


This page last edited on 10 May 2017.

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