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Context-dependent piano music transcription with convolutional sparse coding

United States Patent

9,779,706
October 3, 2017
View the Complete Patent at the US Patent & Trademark Office
Los Alamos National Laboratory - Visit the Technology Transfer Division Website
The present disclosure presents a novel approach to automatic transcription of piano music in a context-dependent setting. Embodiments described herein may employ an efficient algorithm for convolutional sparse coding to approximate a music waveform as a summation of piano note waveforms convolved with associated temporal activations. The piano note waveforms may be pre-recorded for a particular piano that is to be transcribed and may optionally be pre-recorded in the specific environment where the piano performance is to be performed. During transcription, the note waveforms may be fixed and associated temporal activations may be estimated and post-processed to obtain the pitch and onset transcription. Experiments have shown that embodiments of the disclosure significantly outperform state-of-the-art music transcription methods trained in the same context-dependent setting, in both transcription accuracy and time precision, in various scenarios including synthetic, anechoic, noisy, and reverberant environments.
Cogliati; Andrea (Rochester, NY), Duan; Zhiyao (Penfield, NY), Wohlberg; Brendt Egon (Santa Fe, NM)
University of Rochester (Rochester, NY), Los Alamos National Security, LLC (Los Alamos, NM)
15/ 046,724
February 18, 2016
STATEMENT REGARDING FEDERALLY FUNDED RESEARCH This invention was made with government support under DE-AC52-06NA25396 awarded by the Department of Energy. The government has certain rights in the invention.