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Parziale A, Capriolo G, Marcelli A. One Step Is Not Enough: A Multi-Step Procedure for Building the Training Set of a Query by String Keyword Spotting System to Assist the Transcription of Historical Document. J Imaging. 2020;6(10)doi: 10.3390/jimaging6100109.
Parziale, A., Capriolo, G., & Marcelli, A. (2020). One Step Is Not Enough: A Multi-Step Procedure for Building the Training Set of a Query by String Keyword Spotting System to Assist the Transcription of Historical Document. Journal of imaging, 6(10), . https://doi.org/10.3390/jimaging6100109
Parziale, Antonio, et al. "One Step Is Not Enough: A Multi-Step Procedure for Building the Training Set of a Query by String Keyword Spotting System to Assist the Transcription of Historical Document." Journal of imaging vol. 6,10 (2020). doi: https://doi.org/10.3390/jimaging6100109
Parziale A, Capriolo G, Marcelli A. One Step Is Not Enough: A Multi-Step Procedure for Building the Training Set of a Query by String Keyword Spotting System to Assist the Transcription of Historical Document. J Imaging. 2020 Oct 13;6(10). doi: 10.3390/jimaging6100109. PMID: 34460550; PMCID: PMC8321172.
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J Imaging. 2020 Oct 13;6(10). doi: 10.3390/jimaging6100109.

One Step Is Not Enough: A Multi-Step Procedure for Building the Training Set of a Query by String Keyword Spotting System to Assist the Transcription of Historical Document.

Journal of imaging

Antonio Parziale, Giuliana Capriolo, Angelo Marcelli

Affiliations

  1. Department of Information and Electrical Engineering and Applied Mathematics, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano (SA), Italy.
  2. Department of Cultural Heritage, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano (SA), Italy.

PMID: 34460550 PMCID: PMC8321172 DOI: 10.3390/jimaging6100109

Abstract

Digital libraries offer access to a large number of handwritten historical documents. These documents are available as raw images and therefore their content is not searchable. A fully manual transcription is time-consuming and expensive while a fully automatic transcription is cheaper but not comparable in terms of accuracy. The performance of automatic transcription systems is strictly related to the composition of the training set. We propose a multi-step procedure that exploits a Keyword Spotting system and human validation for building up a training set in a time shorter than the one required by a fully manual procedure. The multi-step procedure was tested on a data set made up of 50 pages extracted from the Bentham collection. The palaeographer that transcribed the data set with the multi-step procedure instead of the fully manual procedure had a time gain of 52.54%. Moreover, a small size training set that allowed the keyword spotting system to show a precision value greater than the recall value was built with the multi-step procedure in a time equal to 35.25% of the time required for annotating the whole data set.

Keywords: assisted transcription; automatic document processing; cultural heritage; digital transformation; handwritten documents; historical documents; keyword spotting; training set

References

  1. IEEE Trans Pattern Anal Mach Intell. 2009 May;31(5):855-68 - PubMed
  2. IEEE Trans Pattern Anal Mach Intell. 2011 Apr;33(4):767-79 - PubMed
  3. IEEE Trans Pattern Anal Mach Intell. 2011 Oct;33(10):2066-80 - PubMed

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