Subject: Re: pitch tracking From: James Beauchamp <beaucham(at)UXH.CSO.UIUC.EDU> Date: Fri, 25 Feb 1994 18:01:24 -0600Charles Tassoni writes: >Can anybody tell me how good the latest generation of pitchtrackers >is? Is there, for example, a pitchtracker that can take a melodic dictation >from a human singer? That is, if I sing a melodic sequence and two musicians >produce the same transcription of that sequence, is there an algorithm that >can als output that same transcription? > If accurate transcribers haven't been developed, what are some of the >problems that have prevented their development? Rob Maher and I have done some work in the pitchtracking area which we report in a paper coming out in JASA very soon (March?). Judith Brown has published several JASA papers on the subject. In terms of converting the fundamental frequency data to actual notes on staves, this could be done by converting this data into a MIDI stream and then inputing it to a computer notation program such as SCORE or FINALE. Some complete self-contained transcribers of solo passages have been configured I'm sure. J.A. Moorer had a thesis on this in the 70's (Stanford ~75) and Piszczalski and Galler at U. of Mich. developed a computer system in the late 70's Lippold Haken had a real time system going at the Univ. of Illinois CERL Music Group a few years back. There are probably some commercial systems, as I hear that accompanying systems are available for musicians. I think none of these systems have been totally successful. On rapid passages there are lots of problems with interference from reverberation and/or various noises of articulation during transitions between notes. The narrower the pitch range, the easier the problem is to solve, but in music, you can have leaps of two octaves or more. Octave errors are among the most common that occur in these systems. With duets there are problems of separation, particularly when harmonics of the two voices happen to collide. There was a special session on music FF tracking at the fall 1992 ASA meeting in New Orleans. No one had a definitive result, but there were lots of great partial results. Maximum likelihood looks like a promising technique. Neural nets may help. Jim Beauchamp UIUC