•    Freeware
  •    Shareware
  •    Research
  •    Localization Tools 20
  •    Publications 707
  •    Validators 2
  •    Mobile Apps 22
  •    Fonts 31
  •    Guidelines/ Draft Standards 3
  •    Documents 13
  •    General Tools 38
  •    NLP Tools 105
  •    Linguistic Resources 255
N-gram language models and lexicon-based word-recognition are popular methods in the literature to improve recognition accuracies of online and offline handwritten data. However, there are very few works that deal with application of these techniques on online Tamil handwritten data. In this paper, we explore methods of developing symbol-level language models and a lexicon from a large Tamil text corpus and their application to improving symbol and word recognition accuracies. On a test database of around 2000 words, we find that bigram language models improve symbol (3%) and word recognition (8%) accuracies and while lexicon methods offer much greater improvements (30%) in terms of word recognition, there is a large dependency on choosing the right lexicon. For comparison to lexicon and language model based methods, we have also explored re-evaluation techniques which involve the use of expert classifiers to improve symbol and word recognition accuracies.

Added on August 8, 2014


  More Details
  • Product Type : Research Paper
  • License Type : Freeware
  • System Requirement : Not Applicable
  • Author : Suresh Sundaram, Bhargava Urala K, A. G. Ramakrishnan
Author Community Profile :
Similar / Suggested Resources