Recent Submissions

  • Towards Complete Polyphonic Music Transcription: Integrating Multi-Pitch Detection and Rhythm Quantization 

    Nakamura, E; BENETOS, E; Yoshii, K; DIXON, S; IEEE International Conference on Acoustics, Speech and Signal Processing (IEEE, 2018-04)
    Most work on automatic transcription produces "piano roll" data with no musical interpretation of the rhythm or pitches. We present a polyphonic transcription method that converts a music audio signal into a human-readable ...
  • Risky business: Disfluency as a design strategy 

    BIN, SMA; BRYAN-KINNS, N; MCPHERSON, AP (New Interfaces for Musical Expression, 2018-06-04)
    This paper presents a study examining the effects of disfluent design on audience perception of digital musical instrument (DMI) performance. Disfluency, defined as a barrier to effortless cognitive processing, has been ...
  • A Supervised Classification Approach for Note Tracking in Polyphonic Piano Transcription 

    Valero-Mas, JJ; BENETOS, E; Iñesta, JM (Taylor & Francis (Routledge), 2018-03)
    In the field of Automatic Music Transcription, note tracking systems constitute a key process in the overall success of the task as they compute the expected note-level abstraction out of a frame-based pitch activation ...
  • DMRN+12: Digital Music Research Network Workshop Proceedings 2017 

    KUDUMAKIS, P; SANDLER, M; DMRN+12: Digital Music Research Network Workshop 2017 (Centre for Digital Music, Queen Mary University of London, 2017)
  • Transfer learning for music classification and regression tasks 

    CHOI, K; FAZEKAS, G; SANDLER, M; kyunghyun, C; The 18th International Society of Music Information Retrieval (ISMIR) Conference (International Society of Music Information, 2017)
    In this paper, we present a transfer learning approach for music classification and regression tasks. We propose to use a pre-trained convnet feature, a concatenated feature vector using the activations of feature maps ...
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