Automatic Conflict Detection in Police Body-Worn Audio


Automatic conflict detection has grown in relevance with the advent of body-worn technology, but existing metrics such as turn-taking and overlap are poor indicators of conflict in police-public interactions. Moreover, standard techniques to compute them fall short when applied to such diversified and noisy contexts. We develop a pipeline catered to this task combining adaptive noise removal, non-speech filtering and new measures of conflict based on the repetition and intensity of phrases in speech. We demonstrate the effectiveness of our approach on body-worn audio data collected by the Los Angeles Police Department.

International Conference on Acoustics, Speech, and Signal Processing
Jelena Trisovic
Jelena Trisovic
Ph.D. Student

My research interests include signal processing, machine learning and system control.