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Start Date

30-4-2021 12:00 AM

Document Type

Oral Presentation

Department

Computer Sciences

Faculty Mentor

David Bantz, PhD

Keywords

Ambient sound, Audio analysis, Spectrum constraints, Dangerous sounds, Python, Real-time data analysis, Animated data display, Computer science, Data visualization, Spectrometer

Abstract

Acoustic data offers much information about environmental conditions. They can indicate a harmful environment if certain frequencies are present or too loud, or indicate irregularities in systems when unusual sounds occur. To evaluate the acoustic environment, an application was created to monitor the amplitude and frequency of ambient conditions and compare them with user-defined templates to ensure measurements fall within a desired range. The application was made using the Python computer language with ease of use in mind. Users had to be able to create frequency templates from ambient sound samples or by manually setting desired thresholds. The application could then be left on its own to compare incoming audio with the templates, creating an incident report and sample for user analysis. This application could be beneficial to evaluate harmful levels of sound and any environment where varying frequencies can indicate a required action.

Hayes & Soule Audio Analysis Powerpoint.pdf (3622 kB)
Application for User-Defined Ambient Audio Analysis - slides

Application-for-User-Defined-Ambient-Audio-Analysis_report.pdf (117 kB)
Application for User-Defined Ambient Audio Analysis - report

TM2021_Hayes-Soule_transcript.txt (11 kB)
Application for User-Defined Ambient Audio Analysis - transcript

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Apr 30th, 12:00 AM

Application for User-Defined Ambient Audio Analysis

Acoustic data offers much information about environmental conditions. They can indicate a harmful environment if certain frequencies are present or too loud, or indicate irregularities in systems when unusual sounds occur. To evaluate the acoustic environment, an application was created to monitor the amplitude and frequency of ambient conditions and compare them with user-defined templates to ensure measurements fall within a desired range. The application was made using the Python computer language with ease of use in mind. Users had to be able to create frequency templates from ambient sound samples or by manually setting desired thresholds. The application could then be left on its own to compare incoming audio with the templates, creating an incident report and sample for user analysis. This application could be beneficial to evaluate harmful levels of sound and any environment where varying frequencies can indicate a required action.

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