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Considerations for the Next Generation of Singing Tutor Systems

Recently software systems have been proposed to accelerate the progress of singing beginners. The basics of these systems are: the pitch of the sung notes is detected and algorithmic errors removed. Then, an alignment is made with a melodic ground truth, often as a midi representation, using techniques including Dynamic Time Warping and Hidden Markov Models. Although results have been reasonable, significant drawbacks to these alignment schemes include how a “musically acceptable” alignment can be identified, dynamic singer behavior, multiple repeated notes, and dealing with omitted or extra notes. To this end an improved singing analysis system structure is proposed that includes psychoacoustic models and intelligent decision making. Justification is given along with a description of a structured evaluation procedure.

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