Method and system for automatic transcription correction

Image analysis – Editing – error checking – or correction – Correcting alphanumeric recognition errors

Patent

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

382155, 382159, 382161, 382215, 382226, 382230, G06K 903, G06K 968

Patent

active

058839860

ABSTRACT:
A method and system for automatically modifying an original transcription produced as the output of a recognition operation produces a second, modified transcription, such as, for example, automatically correcting an errorful transcription produced by an OCR operation. The invention uses information in an input text image of character images and in an original transcription associated with the input text image to modify aspects of a formal image source model that models as a grammar the spatial image structure of a set of text images. A recognition operation is then performed on the input text image using the modified formal image source model to produce a second, modified transcription. When the original transcription is errorful, the second transcription is a corrected transcription. Several aspects of the formal image source model may be modified; in particular, character templates to be used in the recognition operation are trained in the font of the glyphs occurring in the input text image. When errors in the original transcription are caused by matching glyphs against templates that are inadequately specified for the given input text image, the subsequently performed recognition operation on the text image using the trained, font-specific character templates produces a more accurate transcription.

REFERENCES:
patent: 3167746 (1965-01-01), Reines et al.
patent: 3548202 (1970-12-01), Ide et al.
patent: 3969700 (1976-07-01), Bollinger et al.
patent: 4599692 (1986-07-01), Tan et al.
patent: 4654875 (1987-03-01), Srihari et al.
patent: 4769716 (1988-09-01), Casey et al.
patent: 4979227 (1990-12-01), Mittelbach et al.
patent: 5020112 (1991-05-01), Chou
patent: 5048097 (1991-09-01), Gaborski et al.
patent: 5048113 (1991-09-01), Yamagata et al.
patent: 5257328 (1993-10-01), Shimizu
patent: 5303313 (1994-04-01), Mark et al.
patent: 5321773 (1994-06-01), Kopec et al.
patent: 5438630 (1995-08-01), Chou
patent: 5526444 (1996-06-01), Kopec et al.
patent: 5544260 (1996-08-01), Chefalas
E.M. Riseman and A.R. Hanson, "A Contextual Postprocessing System for Error Correction Using Binary n-Grams", IEEE Transactions on Computers, May 174, pp. 480-493.
J.R. Ullman, "A Binary n-Gram Technique for Automatic Correction of Substitution, Deletion, Insertion and Reversal Errors in Words", The Computer Journal, 1977, pp. 141-147.
J.J. Hull and S.N. Srihari, Experiments in Text Recognition with Binary n-Gram and Viterbi Algorithms, IEEE Transactions on Pattern Analysis and Machine Intelligence, Sep. 1982, pp. 520-530.
G. Kopec, "Least-Squares Font Metric Estimation from Images", in IEEE Transactions on Image Processing, Oct., 1993, pp. 510-519.
G. Kopec and P. Chou, "Document Image Decoding Using Markov Source Models." in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 16, No. 6, Jun. 1994, pp. 602-617.
Huang, Ariki and Jack, Hidden Markov Models for Speech Recognition Edinburgh University Press, 1990, chapters 2, 5 and 6, pp. 10-51; 136-166; and 167-185.
L. Rabiner and B. Juang, "An Introduction to Hidden Markov Models", in IEEE ASSP Magazine, Jan. 1986, at pp. 4-16.
L. Rabiner, "A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition", in Proceedings of the IEEE, vol. 77, No. 2, Feb., 1989, at pp. 257-285.
H.S. Baird, "A Self-Correcting 100-Font Classifier," in SPIE vol. 2181 Document Recognition, 1994, pp. 106-115.
S. Kuo and O.E. Agazzi, "Keyword spotting in poorly printed documents using pseudo 2D hidden Markov models," in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 16, No. 8, Aug., 1994, pp. 842-848.
C. Bose and S. Kuo, "Connected and degraded text recognition using a hidden Markov model," in Proceedings of the International Conference on Pattern Recognition, Netherlands, Sep. 1992, pp. 116-119.
P.A. Chou and G. E. Kopec, "A Stochastic Attribute Grammar Model of Document Production and Its Use in Document Image Decoding", Document Recognition II, Luc M. Vincent, Henry S. Baird, Editors, Proceedings SPIE 2422, pp. 66-73 (Feb., 1995).
A. Kam and G. Kopec, "Separable source models for document image decoding", Document Recognition II, Luc M. Vincent, Henry S. Baird, Editors, Proceedings SPIE 2422, pp. 84-97 (Feb., 1995).
A. Kam, "Heuristic Document Image Decoding Using Separable Markov Models", S.M. Thesis, Massachusetts Institute of Technology, Cambridge, MA, Jun., 1993.
M. Brown and J. Wilpon, "A grammar compiler for connected speech recognition," in IEEE Trans. on Signal Processing, vol. 39, No. 1, Jan. 1991, pp. 17-28.
K. Y. Wong, R. G. Casey and F.M. Wahl, "Document Analysis System", IBM J Res Develop., vol. 26, No. 6, Nov. 1982, pp. 647-656.
Thomas M. Breuel, "A system for the off-line recognition of handwritten text" in Proceedings of the International Conference on Pattern Recognition (ICPR), Oct. 9-13, 1994, Jerusalem, Israel, pp. 129-134.
National Science Foundation (NSF) Grant Proposal for NSF Program Digital Libraries NSF 93-141 Feb. 4, 1994, submitted by the Regents of the University of California, Berkeley, document date Jan. 24, 1994, p. i-xi, 2-5, 36-37, 101, and 106.
"Automatic Switching of Recognition Character Set," IBM Technical Disclosure Bulletin, vol. 37, No. 04B, Apr. 1994, p. 41, Armonk, NY.
European Search Report for EPO counterpart application No. 96303900.3, Jul. 23, 1997.
H.S. Baird, "Self-Correcting 100-font Classifier," in SPIE. vol. 2181 Document Recognition, 1994, pp. 106-115.
G. Kopec and P. Chou, Document Image Decoding Using Markov Source Models in IEEE Trans on Pattern Anal and Machine Intel, vol. 16 Jun. 1994 pp. 602-617.

LandOfFree

Say what you really think

Search LandOfFree.com for the USA inventors and patents. Rate them and share your experience with other people.

Rating

Method and system for automatic transcription correction does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Method and system for automatic transcription correction, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Method and system for automatic transcription correction will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFUS-PAI-O-824260

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.