Date of Graduation

5-2017

Document Type

Thesis

Degree Name

Bachelor of Science

Degree Level

Undergraduate

Department

Computer Science and Computer Engineering

Advisor

Gauch, John

Reader

Gauch, John

Second Reader

Gashler, Michael

Third Reader

Patitz, Matthew

Abstract

This paper seeks to establish the validity and potential benefits of using existing computer vision techniques on audio samples rather than traditional images in order to consistently and accurately identify a song of origin from a short audio clip of potentially noisy sound. To do this, the audio sample is first converted to a spectrogram image, which is used to generate SURF features. These features are compared against a database of features, which have been previously generated in a similar fashion, in order to find the best match. This algorithm has been implemented in a system that can run as a server, processing “query” clips as they come in and returning to the end user a specific song which matches the input query audio.