Physical Sciences and Mathematics Commons^™

Automatic Music Transcription With Convolutional Neural Networks Using Intuitive Filter Shapes, Jonathan Sleep

Master's Theses

This thesis explores the challenge of automatic music transcription with a combination of digital signal processing and machine learning methods. Automatic music transcription is important for musicians who can't do it themselves or find it tedious. We start with an existing model, designed by Sigtia, Benetos and Dixon, and develop it in a number of original ways. We find that by using convolutional neural networks with filter shapes more tailored for spectrogram data, we see better and faster transcription results when evaluating the new model on a dataset of classical piano music. We also find that employing better practices shows …

Using Spectral Analysis To Evaluate Flute Tone Quality, Ron Yorita

Master's Theses

Many skilled flutists place a high priority on "good" tone quality, or timbre. Timbre can be defined as the audible difference in character that a listener perceives for two notes played at the same pitch. Different timbres are determined by the combination and balance of harmonics that comprise a note. Unlike pitch and rhythm, timbre is difficult to objectively quantify. This project explores (1) how tone quality is described by skilled flutists, (2) whether the harmonic spectrum has some correlation with tone quality, (3) whether certain harmonic spectra are preferred, or considered "good".

Thirty-one flutists ranging from high school students …

Functional Reactive Musical Performers, Justin M. Phillips

Master's Theses

Computers have been assisting in recording, sound synthesis and other fields of music production for quite some time. The actual performance of music continues to be an area in which human players are chosen over computer performers. Musical performance is an area in which personalization is more important than consistency. Human players play with each other, reacting to phrases and ideas created by the players that they are playing with. Computer performers lack the ability to react to the changes in the performance that humans perceive naturally, giving the human players an advantage over the computer performers.

This thesis creates …