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AMP Project Update: Leveraging Machine Learning and Human Expertise for AV Collections Access

Home / Topics / Information Access & Retrieval / AMP Project Update: Leveraging Machine Learning and Human Expertise for AV Collections Access

March 25, 2020

Jon W. Dunn
Assistant Dean for Library Technologies
Indiana University

Shawn Averkamp
Senior Consultant
AVP

Academic libraries and archives are dealing with increasing numbers of digital audio and video (AV) files, acquired through digitization of analog collections and acquisition of born-digital AV resources. While the emergence of low-cost storage options and maturity of streaming platforms have made it easier to store and deliver AV, these collections often lack metadata needed to make them discoverable and usable by researchers and other users. The Indiana University Libraries have been working with partners at the University of Texas at Austin, New York Public Library, and digital consultant AVP to develop an open-source software platform, known as AMP (Audiovisual Metadata Platform), that leverages automated machine learning-based tools together with human expertise to build workflows to create and augment metadata for AV resources that enable discovery, rights determination, and use. We will present an update on the progress of the AMP project and its successes and challenges to date, including issues of workflows and integration of open-source and cloud-based machine learning tools. This presentation follows on a presentation given at CNI in spring 2018 on the planning project that led to this current phase of work, which is generously funded by a grant from The Andrew W. Mellon Foundation.

Presentation

https://go.iu.edu/amppd

 

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Filed Under: Information Access & Retrieval, Metadata, Project Briefing Pages, Special Collections, Spring 2020 Project Briefings
Tagged With: cni2020spring, Project Briefings & Plenary Sessions, Videos

Last updated:  Thursday, December 2nd, 2021

 

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