Work

Automatic Conflict Detection in Police Body-Worn Audio

Year: 2018

Type: conference-paper

Abstract: 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.

Source: IEEE International Conference on Acoustics Speech and Signal Processing

DOI: 10.1109/icassp.2018.8461425

Authors: Alistair Letcher, Jelena Trisovic, Collin Cademartori, Xi Chen, Jason Xu

Institutions: University of Oxford, University of Belgrade, Brown University, Carleton College, University of California, Los Angeles

Language: English

Topic: Speech Recognition and Synthesis

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Peace, justice, and strong institutions

Open Access status: green

OpenAlex ID: W2963801941

FWCI: 0.177

Cites: 15

Cited by: 3

Related to: 10