This beginner’s audio analysis workshop is part of the HiPSTAS (High Performance Sound Technologies for Access and Scholarship) project. We will introduce participants to essential issues that DH scholars, who are often more familiar with working with text, must face in understanding the nature of audio texts such as poetry readings, oral histories, speeches, and radio programs. Understanding what users of sound collections want to do and what kinds of research questions are viable in the context of audio analysis is only a first step. We will also introduce participants to techniques in advanced computational analysis such as annotation, classification, and visualization that are essential to machine learning workflows, using tools such as Sonic Visualiser, ARLO, and pyAudioAnalysis. In the workshop, we will walk through a sample workflow for audio machine learning. This workflow includes developing a tractable machine-learning problem, creating and labeling audio segments, running machine learning queries, and validating results. As a result of the workshop, participants will be able to consider potential use cases for which they might use advanced technologies to augment their research on sound, and, in the process, they will also be introduced to the possibilities of sharing workflows for enabling such scholarship with archival sound recordings at their home institutions. The datasets and tools with which they will work will be free software available for continued study after the workshop.

This workshop is open to any scholars who are interested in learning to use machine learning and visualization to analyze audio files of interest to the humanities such as poetry readings, oral histories, speeches, and radio programs. There are no prerequisites but familiarity with an audio collection of interest is useful to help ground participants in their own use cases.

Participants are expected to bring bring a laptop (any operating system) as well as headphones or earbuds. All tools used in this workshop are open source or free software. An audio corpus will be provided for the hands-on demo.

Clement is Assistant Professor in the School of Information at UT Austin. She studies the dynamic interplay of digital information systems and scholarly research in the humanities.