Date Thesis Awarded


Access Type

Honors Thesis -- Access Restricted On-Campus Only

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.

On-Campus Access Only