Automatic Music Transcription Leveraging Generalized Cepstral Features and Deep Learning - researchr publication related

researchr

You are not signed in
Sign in
Sign up

Yu-Te Wu, Berlin Chen, Li Su. Automatic Music Transcription Leveraging Generalized Cepstral Features and Deep Learning. In 2018 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2018, Calgary, AB, Canada, April 15-20, 2018. pages 401-405, IEEE, 2018. [doi]

The following publications are possibly variants of this publication:

Automatic Drum Transcription Using the Student-Teacher Learning Paradigm with Unlabeled Music DataChih-Wei Wu, Alexander Lerch. ismir 2017: 613-620 [doi]

Learned Features for the Assessment of Percussive Music PerformancesWu, Chih-Wei, Alexander Lerch. In Proceedings of the International Conference on Semantic Computing (ICSC). 2018:

Learned Features for the Assessment of Percussive Music PerformancesWu, Chih-Wei, Alexander Lerch. In Proceedings of the International Conference on Semantic Computing ({ICSC}). 2018:

Towards the Objective Assessment of Music PerformancesWu, Chih-Wei, Gururani, Siddharth, Laguna, Christopher, Pati, Ashis, Vidwans, Amruta, Alexander Lerch. In Proceedings of the International Conference on Music Perception and Cognition (ICMPC). 2016: 99-103

A Review of Automatic Drum TranscriptionWu, Chih-Wei, Dittmar, Christian, Southall, Carl, Vogl, Richard, Widmer, Gerhard, Hockman, Jason A, Muller, Meinard, Alexander Lerch. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 26(9):1457-1483, 2018. [doi]

Objective Descriptors for the Assessment of Student Music PerformancesAmruta Vidwans, Siddharth Gururani, Chih-Wei Wu, Vinod Subramanian, Rupak Swaminathan, Alexander Lerch. semanticaudio 2017: [doi]

runs on WebDSL