Automatic Transcription of Piano Music
نویسنده
چکیده
A hidden Markov model approach to piano music transcription is presented. The main difficulty in applying traditional HMM techniques is the large number of chord hypotheses that must be considered. We address this problem by using a trained likelihood model to generate reasonable hypotheses for each frame and construct the search graph out of these hypotheses. Results are presented using a recording of a movement from Mozart’s Sonata 18, K. 570.
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تاریخ انتشار 2002