Handling out-of-vocabulary words and recognition errors based on word linguistic context for handwritten sentence recognition

Proceedings of the International Conference on Document Analysis and Recognition, ICDAR

Volumn , Issue , 2009, Pages 466-470

  Quiniou, Solen ^a   Cheriet, Mohamed ^a   Anquetil, Eric ^b  

^a ÉCOLE DE TECHNOLOGIE SUPÉRIEURE   (Canada)

^b CAMPUS DE BEAULIEU   (France)

Author keywords

[No Author keywords available]

Indexed keywords

LANGUAGE MODEL; LINGUISTIC INFORMATION; N-GRAM MODELS; OUT-OF-VOCABULARY WORDS; PART-OF-SPEECH TAGS; POST PROCESSING; RECOGNITION ERROR; SVM CLASSIFIERS; WORD ERROR RATE; WORD POSTERIOR PROBABILITY; WORD RECOGNITION;

COMPUTATIONAL LINGUISTICS; ERROR DETECTION; QUERY LANGUAGES;

CHARACTER RECOGNITION;

EID: 71249093423     PISSN: 15205363     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDAR.2009.78     Document Type: Conference Paper

References (16)

1. I. Bazzi. Modelling Out-Of-Vocabulary Words for Robust Speech Recognition. PhD thesis, MIT, 2002.
2. R. Bertolami, M. Zimmermann, and H. Bunke. Rejection strategies for offline handwritten text recognition. Pattern Recognition Letters, 27:2005-2012, 2006.
3. M. Bisani and H. Ney. Open vocabulary speech recognition with flat hybrid models. In Interspeech'05, pages 725-728.
4. S. Carbonnel and E. Anquetil. Lexicon Organization and String Edit Distance Learning for Lexical Post-Processing in Handwriting Recognition. In IWFHR'04, pages 462-467.
5. W. Francis and H. Kucera. Brown Corpus Manual. Brown University, 1979.
6. D. Hillard and M. Ostendorf. Compensating forWord Posterior Estimation Bias in Confusion Networks. In ICASSP'06, pages 1153-1156.
7. M. Liwicki and H. Bunke. Handwriting Recognition of Whiteboard Notes - Studying the Influence of Training Set Size and Type. IJPRAI, 21(1):83-98, 2007.
8. L. Mangu. Finding Consensus in Speech Recognition. PhD thesis, Johns Hopkins University, 2000.
9. S. Marukatat, T. Artières, and P. Gallinari. Rejection Measures for Handwriting Sentence Recognition. In IWFHR'02, pages 24-29.
10. T. Niesler. Category-Based Statistical Language Models. PhD thesis, University of Cambridge, 1997.
11. J. Pitrelli, J. Subrahmonia, and M. Perrone. Confidence Modeling for Handwriting Recognition: Algorithms and Applications. IJDAR, 8(1):35-46, 2006.
12. S. Quiniou and E. Anquetil. Use of a Confusion Network to Detect and Correct Errors in an On-line Handwritten Sentence Recognition System. In ICDAR'07, pages 382-386.
13. S. Quiniou, F. Bouteruche, and E. Anquetil. Word Extraction Associated with a Confidence Index for On-Line Handwritten Sentence Recognition. IJPRAI, 2009. to appear.
14. M. Shilman, Z. Wei, S. Raghupathy, P. Simard, and D. Jones. Discerning Structure from Freeform Handwritten Notes. In ICDAR'03, pages 60-65.
15. A. Stolcke. SRILM - An Extensible Language Modeling Toolkit. In ICSLP'02, pages 901-904.
16. A. Vinciarelli, S. Bengio, and H. Bunke. Offline Recognition of Unconstrained Handwritten Texts using HMMs and Statistical Language Models. PAMI, 26(6):709-720, 2004.