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Multimodal interactive handwritten t...

Romero, Verónica.

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Multimodal interactive handwritten text transcription

Record Type:	Electronic resources : Monograph/item
Title/Author:	Multimodal interactive handwritten text transcription/ Verónica Romero, Alejandra Héctor Toselli, Enrique Vidal.
Author:	Romero, Verónica.
other author:	Toselli, Alejandro Héctor.
Published:	Singapore :World Scientific Pub, : 2012.,
Description:	1 online resource (xi, 167 p.) :ill.
[NT 15003449]:	1. Preliminaries. 1.1. Introduction. 1.2. State of the art. 1.3. Formal background. 1.4. Assessing computer assisted transcription of handwritten text images -- 2. Corpora. 2.1. Introduction. 2.2. CS. 2.3. ODEC. 2.4. IAMDB. 2.5. UNIPEN -- 3. Handwritten text recognition. 3.1. Introduction. 3.2. Off-line handwritten text recognition. 3.3. On-line handwritten text recognition. 3.4. Summary and conclusions -- 4. Computer assisted transcription of handwritten text images. 4.1. Introduction. 4.2. Formal framework. 4.3. Adapting the language model. 4.4. Searching. 4.5. Increasing interaction ergonomy. 4.6. Interacting at the character level. 4.7. Experimental framework. 4.8. Results. 4.9. Conclusions and future work -- 5. Multimodal computer assisted transcription of handwritten text images. 5.1. Introduction. 5.2. Formal framework. 5.3. Adapting the language model. 5.4. Searching. 5.5. Experimental framework. 5.6. Results. 5.7. Conclusions -- 6. A web-based demonstrator of interactive multimodal transcription. 6.1. Introduction. 6.2. User interaction protocol. 6.3. System description. 6.4. Evaluation. 6.5. Results and discussion. 6.6. Conclusions -- 7. Conclusions and outlook. 7.1. Conclusions. 7.2. Outlook.
Subject:	Writing - Data processing. -
Online resource:	http://www.worldscientific.com/worldscibooks/10.1142/8394#t=toc
ISBN:	9789814390347 (electronic bk.)

Multimodal interactive handwritten text transcription
Romero, Verónica.

Multimodal interactive handwritten text transcription[electronic resource] /Verónica Romero, Alejandra Héctor Toselli, Enrique Vidal. - Singapore :World Scientific Pub,2012. - 1 online resource (xi, 167 p.) :ill. - Series in machine perception and artificial intelligence ;v. 80. - Series in machine perception and artificial intelligence ;v. 74..

Includes bibliographical reference (p. 155-164) and index.

1. Preliminaries. 1.1. Introduction. 1.2. State of the art. 1.3. Formal background. 1.4. Assessing computer assisted transcription of handwritten text images -- 2. Corpora. 2.1. Introduction. 2.2. CS. 2.3. ODEC. 2.4. IAMDB. 2.5. UNIPEN -- 3. Handwritten text recognition. 3.1. Introduction. 3.2. Off-line handwritten text recognition. 3.3. On-line handwritten text recognition. 3.4. Summary and conclusions -- 4. Computer assisted transcription of handwritten text images. 4.1. Introduction. 4.2. Formal framework. 4.3. Adapting the language model. 4.4. Searching. 4.5. Increasing interaction ergonomy. 4.6. Interacting at the character level. 4.7. Experimental framework. 4.8. Results. 4.9. Conclusions and future work -- 5. Multimodal computer assisted transcription of handwritten text images. 5.1. Introduction. 5.2. Formal framework. 5.3. Adapting the language model. 5.4. Searching. 5.5. Experimental framework. 5.6. Results. 5.7. Conclusions -- 6. A web-based demonstrator of interactive multimodal transcription. 6.1. Introduction. 6.2. User interaction protocol. 6.3. System description. 6.4. Evaluation. 6.5. Results and discussion. 6.6. Conclusions -- 7. Conclusions and outlook. 7.1. Conclusions. 7.2. Outlook.

This book presents an interactive multimodal approach for efficient transcription of handwritten text images. This approach, rather than full automation, assists the expert in the recognition and transcription process. Until now, handwritten text recognition (HTR) systems are far from being perfect and heavy human intervention is often required to check and correct the results of such systems. The interactive scenario studied in this book combines the efficiency of automatic handwriting recognition systems with the accuracy of the experts, leading to a cost-effective perfect transcription of the handwritten text images. The interactive system here allows the user to repeatedly interact with the system. Hence, the quality and ergonomy of the interactive process is crucial for the success of the system. Moreover, more ergonomic multimodal interfaces are used to obtain an easier and more comfortable human-machine interaction.

ISBN: 9789814390347 (electronic bk.)Subjects--Uniform Titles:

Natural language processing.
Subjects--Topical Terms:

2150965
Writing
--Data processing.

LC Class. No.: QA76.9.U83 / R66 2012eb

Dewey Class. No.: 006.425

Multimodal interactive handwritten text transcription
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020 $a 9789814390347 (electronic bk.)
020 $a 9814390348 (electronic bk.)
020 $a 1283593734 (electronic bk.)
020 $a 9781283593731 (electronic bk.)
020 $z 9789814390330
020 $z 981439033X
035 $a (OCoLC)810933234 $z (OCoLC)810317529 $z (OCoLC)811504361 $z (OCoLC)817811965
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040 $a N $b eng $c N $d IDEBK $d E7B $d OCLCQ $d STF $d OCLCF $d B24X7 $d COO $d YDXCP $d DEBSZ $d MHW $d EBLCP $d CDX $d OCLCQ
050 4 $a QA76.9.U83 $b R66 2012eb
082 0 4 $a 006.425 $2 23
100 1 $a Romero, Verónica. $3 2150962
245 1 0 $a Multimodal interactive handwritten text transcription $h [electronic resource] / $c Verónica Romero, Alejandra Héctor Toselli, Enrique Vidal.
260 $a Singapore : $b World Scientific Pub, $c 2012.
300 $a 1 online resource (xi, 167 p.) : $b ill.
490 1 $a Series in machine perception and artificial intelligence ; $v v. 80
504 $a Includes bibliographical reference (p. 155-164) and index.
505 0 $a 1. Preliminaries. 1.1. Introduction. 1.2. State of the art. 1.3. Formal background. 1.4. Assessing computer assisted transcription of handwritten text images -- 2. Corpora. 2.1. Introduction. 2.2. CS. 2.3. ODEC. 2.4. IAMDB. 2.5. UNIPEN -- 3. Handwritten text recognition. 3.1. Introduction. 3.2. Off-line handwritten text recognition. 3.3. On-line handwritten text recognition. 3.4. Summary and conclusions -- 4. Computer assisted transcription of handwritten text images. 4.1. Introduction. 4.2. Formal framework. 4.3. Adapting the language model. 4.4. Searching. 4.5. Increasing interaction ergonomy. 4.6. Interacting at the character level. 4.7. Experimental framework. 4.8. Results. 4.9. Conclusions and future work -- 5. Multimodal computer assisted transcription of handwritten text images. 5.1. Introduction. 5.2. Formal framework. 5.3. Adapting the language model. 5.4. Searching. 5.5. Experimental framework. 5.6. Results. 5.7. Conclusions -- 6. A web-based demonstrator of interactive multimodal transcription. 6.1. Introduction. 6.2. User interaction protocol. 6.3. System description. 6.4. Evaluation. 6.5. Results and discussion. 6.6. Conclusions -- 7. Conclusions and outlook. 7.1. Conclusions. 7.2. Outlook.
520 $a This book presents an interactive multimodal approach for efficient transcription of handwritten text images. This approach, rather than full automation, assists the expert in the recognition and transcription process. Until now, handwritten text recognition (HTR) systems are far from being perfect and heavy human intervention is often required to check and correct the results of such systems. The interactive scenario studied in this book combines the efficiency of automatic handwriting recognition systems with the accuracy of the experts, leading to a cost-effective perfect transcription of the handwritten text images. The interactive system here allows the user to repeatedly interact with the system. Hence, the quality and ergonomy of the interactive process is crucial for the success of the system. Moreover, more ergonomic multimodal interfaces are used to obtain an easier and more comfortable human-machine interaction.
588 0 $a Print version record.
630 0 0 $a Natural language processing. $3 2150966
650 0 $a Writing $x Data processing. $3 2150965
650 0 $a Multimodal user interfaces (Computer systems) $3 1639824
650 0 $a Human-computer interaction. $3 560071
700 1 $a Toselli, Alejandro Héctor. $3 2150963
700 1 $a Vidal, Enrique. $3 2150964
830 0 $a Series in machine perception and artificial intelligence ; $v v. 74. $3 1572858
856 4 0 $u http://www.worldscientific.com/worldscibooks/10.1142/8394#t=toc