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Article
Publication date: 1 March 2004

40

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Program, vol. 38 no. 1
Type: Research Article
ISSN: 0033-0337

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Article
Publication date: 1 February 2003

Bronwen Brown

247

Abstract

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Library Review, vol. 52 no. 1
Type: Research Article
ISSN: 0024-2535

Keywords

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Article
Publication date: 1 March 2003

Bronwen Brown

143

Abstract

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Library Review, vol. 52 no. 2
Type: Research Article
ISSN: 0024-2535

Keywords

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Article
Publication date: 1 March 2002

Bronwen Brown

58

Abstract

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Library Review, vol. 51 no. 2
Type: Research Article
ISSN: 0024-2535

Keywords

Content available
Article
Publication date: 1 November 2006

Bob Glass

52

Abstract

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New Library World, vol. 107 no. 11/12
Type: Research Article
ISSN: 0307-4803

Open Access
Article
Publication date: 18 April 2024

Joseph Nockels, Paul Gooding and Melissa Terras

This paper focuses on image-to-text manuscript processing through Handwritten Text Recognition (HTR), a Machine Learning (ML) approach enabled by Artificial Intelligence (AI)…

Abstract

Purpose

This paper focuses on image-to-text manuscript processing through Handwritten Text Recognition (HTR), a Machine Learning (ML) approach enabled by Artificial Intelligence (AI). With HTR now achieving high levels of accuracy, we consider its potential impact on our near-future information environment and knowledge of the past.

Design/methodology/approach

In undertaking a more constructivist analysis, we identified gaps in the current literature through a Grounded Theory Method (GTM). This guided an iterative process of concept mapping through writing sprints in workshop settings. We identified, explored and confirmed themes through group discussion and a further interrogation of relevant literature, until reaching saturation.

Findings

Catalogued as part of our GTM, 120 published texts underpin this paper. We found that HTR facilitates accurate transcription and dataset cleaning, while facilitating access to a variety of historical material. HTR contributes to a virtuous cycle of dataset production and can inform the development of online cataloguing. However, current limitations include dependency on digitisation pipelines, potential archival history omission and entrenchment of bias. We also cite near-future HTR considerations. These include encouraging open access, integrating advanced AI processes and metadata extraction; legal and moral issues surrounding copyright and data ethics; crediting individuals’ transcription contributions and HTR’s environmental costs.

Originality/value

Our research produces a set of best practice recommendations for researchers, data providers and memory institutions, surrounding HTR use. This forms an initial, though not comprehensive, blueprint for directing future HTR research. In pursuing this, the narrative that HTR’s speed and efficiency will simply transform scholarship in archives is deconstructed.

Content available
Article
Publication date: 1 December 1998

Robin Frederick Guy

97

Abstract

Details

Library Review, vol. 47 no. 8
Type: Research Article
ISSN: 0024-2535

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Article
Publication date: 1 December 2004

39

Abstract

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Program, vol. 38 no. 4
Type: Research Article
ISSN: 0033-0337

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Article
Publication date: 1 April 1999

Heather Watkins

65

Abstract

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Librarian Career Development, vol. 7 no. 4
Type: Research Article
ISSN: 0968-0810

Content available
Article
Publication date: 1 January 2005

117

Abstract

Details

Library Hi Tech News, vol. 22 no. 1
Type: Research Article
ISSN: 0741-9058

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