Recent Submissions

  • Deep Learning for Audio Event Detection and Tagging on Low-Resource Datasets 

    Morfi, V; Stowell, D (MDPI, 2018-08-18)
    In training a deep learning system to perform audio transcription, two practical problems may arise. Firstly, most datasets are weakly labelled, having only a list of events present in each recording without any temporal ...
  • Acoustic event detection for multiple overlapping similar sources 

    Stowell, D; Clayton, D (IEEE, 2015-10)
    Many current paradigms for acoustic event detection (AED) are not adapted to the organic variability of natural sounds, and/or they assume a limit on the number of simultaneous sources: often only one source, or one source ...
  • 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 ...
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