Publication Date


Document Type


Committee Members

Valerie Shalin, Ph.D. (Advisor); Sarah Bibyk, Ph.D. (Committee Member); David Lahuis, Ph.D. (Committee Member)

Degree Name

Master of Science (MS)


In this work, I explore the development of computational methods for automatically creating after-action reports of JTAC radio conversations. Prior research has investigated related issues of sentence compression, text summarization, and conversation summarization (Banerjee, Mitra, & Sugiyama, 2015; Clarke & Lapata, 2008; L. Wang & Cardie, 2012; Raffel et al., 2020). However, this work makes limiting assumptions about what features are relevant to a summary and what sources of information should be included. I propose methods that combine knowledge from linguistic, procedural, and domain sources to address these limitations. Results indicate that the proposed model performs better than some of our baseline models, but highlight several challenges of automatically scoring computational summaries, particularly in technical low-resource domains.

Page Count


Department or Program

Department of Psychology

Year Degree Awarded