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A Comparative Study of Neural Models for Polyphonic Music Sequence Transduction
(2019-11-04)
Automatic transcription of polyphonic music remains a challenging task in the field of Music Information Retrieval. One under-investigated point is the post-processing of time-pitch posteriograms into binary piano rolls. ...
A Study On Convolutional Neural Network Based End-To-End Replay Anti-Spoofing
(2018-05-22)
The second Automatic Speaker Verification Spoofing and Countermeasures challenge (ASVspoof 2017) focused on "replay attack" detection. The best deep-learning systems to compete in ASVspoof 2017 used Convolutional Neural ...
Automatic music transcription and ethnomusicology: a user study
(2019-11-04)
Converting an acoustic music signal into music notation using a computer program has been at the forefront of music information research for several decades, as a task referred to as automatic music transcription (AMT). ...
CBF-periDB: A Chinese Bamboo Flute Dataset for Periodic Modulation Analysis
(2019-11-04)
We present CBF-periDB, a dataset of Chinese bamboo flute performances for ecologically valid analysis of periodic modulations in context. The dataset contains monophonic recordings of four types of isolated playing techniques ...
Blending acoustic and language model predictions for automatic music transcription
(2019-11-04)
In this paper, we introduce a method for converting an input probabilistic piano roll (the output of a typical multi-pitch detection model) into a binary piano roll. The task is an important step for many automatic music ...
Adaptive Time–Frequency Scattering for Periodic Modulation Recognition in Music Signals
(2019-11-04)
Vibratos, tremolos, trills, and flutter-tongue are techniques frequently found in vocal and instrumental music. A common feature of these techniques is the periodic modulation in the time--frequency domain. We propose a ...
Onsets, activity, and events: a multi-task approach for polyphonic sound event modelling
(2019-10-25)
State of the art polyphonic sound event detection (SED) systems function as frame-level multi-label classification models. In the context of dynamic polyphony levels at each frame, sound events interfere with each other ...