The Kröller-Müller Museum (KMM) and the Cultural Heritage Agency of the Netherlands (RCE) will deliver case study material to assess the deposition infrastructure with Data Archiving and Networked Services (DANS), and carry out a feasibility study to adapt Automatic Speech Recognition (ASR) to the field of conservation with the Foundation for Open Speech Technology (FOST). Only with time-stamped transcripts, interviews become searchable – raising text-mining potential, cross-referencing, and other use of Artificial Intelligence (AI). The envisioned methodological and technological advancements in using Oral History methodology in conservation research will be of great advantage to technical art history, object diagnosis, conservation decision-making and analysis of cultural heritage at large.

Project Leader

• Dr. Sanneke Stigter (University of Amsterdam, SBMK)

Project Team

• Drs. Margje Leeuwestein (Kröller-Müller Museum)  
• Susanne Kensche, Dipl. Rest. (Kröller-Müller Museum)  
• Drs. Sylvia van Schaik (Cultural Heritage Agency of The Netherlands)  
• Dr. Arjan van Hessen (University of Twente | CLARIAH | FOST)  
• Drs. Widia Mahabier (Data Archiving and Networked Services DANS) 
• Prof. dr. Eric Postma (Tilburg University) 

Project Partners

• University of Amsterdam  
• Kröller-Müller Museum  
• Cultural Heritage Agency of The Netherlands  
• University of Twente  
• Data Archiving and Networked Services (DANS)  
• Tilburg University 
• Foundation Open Speech Technology (FOST) 
• Foundation for the Conservation of Contemporary Art (SBMK)