Date Thesis Awarded


Document Type

Honors Thesis

Degree Name

Bachelors of Science (BS)




Mark K. Hinders

Committee Members

Greg Jerome Bowers

Charles Perdrisat

John Delos


This thesis describes the application of wavelet fingerprinting as a technique to analyze and automatically detect flaws in recorded audio. Specifically, it focuses on time-localized errors in digitized wax cylinder recordings and contemporary digital media. By taking the continuous wavelet transform of various recordings, we created a two-dimensional binary display of audio data. After analyzing the images, we implemented an algorithm to automatically detect where a flaw occurs by comparing the image matrix against the matrix of a known flaw. We were able to use this technique to automatically detect time-localized clicks, pops, and crackles in both cylinders and digital recordings. We also found that while other extra- musical noises, such as coughing, did not leave a traceable mark on the fingerprint, they were distinguishable from samples without the error.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.


Thesis is part of Honors ETD pilot project, 2008-2013. Migrated from Dspace in 2016.