@inproceedings{288c6b4357474ad58d42299ac2120c3f,
title = "Construction of language models for an handwritten mail reading system",
abstract = "This paper presents a system for the recognition of unconstrained handwritten mails. The main part of this system is an HMM recognizer which uses trigraphs to model contextual information. This recognition system does not require any segmentation into words or characters and directly works at line level. To take into account linguistic information and enhance performance, a language model is introduced. This language model is based on bigrams and built from training document transcriptions only. Different experiments with various vocabulary sizes and language models have been conducted. Word Error Rate and Perplexity values are compared to show the interest of specific language models, fit to handwritten mail recognition task.",
keywords = "Hidden Markov Models, Offline Handwriting recognition, handwritten mail, language modeling, n-grams, text-line recognition",
author = "Olivier Morillot and Laurence Likforman-Sulem and Emmanu{\`e}le Grosicki",
year = "2012",
month = feb,
day = "27",
doi = "10.1117/12.911965",
language = "English",
isbn = "9780819489449",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
booktitle = "Proceedings of SPIE-IS and T Electronic Imaging - Document Recognition and Retrieval XIX",
note = "Document Recognition and Retrieval XIX ; Conference date: 25-01-2012 Through 26-01-2012",
}