Precise pitch is important to musicians. We created algorithms for real-time pitch detection that generalise well over a range of single �voiced� musical instruments. A high pitch detection accuracy is achieved whilst maintaining a fast response using a special normalisation of the autocorrelation (SNAC) function and its windowed version, WSNAC. Incremental versions of these functions provide pitch values updated at every input sample. A robust octave detection is achieved through a modified cepstrum, utilising properties of human pitch perception and putting the pitch of the current frame within the context of its full note duration. The algorithms have been tested thoroughly both with synthetic waveforms and sounds from real instruments. A method for detecting note changes using only pitch is also presented.
Furthermore, we describe a real-time method to determine vibrato parameters - higher level information of pitch variations, including the envelopes of vibrato speed, height, phase and centre offset. Some novel ways of visualising the pitch and vibrato information are presented.
Our project �Tartini� provides music students, teachers, performers and researchers with new visual tools to help them learn their art, refine their technique and advance their fields.
| Identifer | oai:union.ndltd.org:ADTP/243046 |
| Date | January 2009 |
| Creators | McLeod, Philip, n/a |
| Publisher | University of Otago. Department of Computer Science |
| Source Sets | Australiasian Digital Theses Program |
| Language | English |
| Detected Language | English |
| Rights | http://policy01.otago.ac.nz/policies/FMPro?-db=policies.fm&-format=viewpolicy.html&-lay=viewpolicy&-sortfield=Title&Type=Academic&-recid=33025&-find), Copyright Philip McLeod |
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