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A study on LSTM networks for polyphonic music sequence modelling
(ISMIR, 2017-10-23)
Neural networks, and especially long short-term memory networks (LSTM), have become increasingly popular for sequence modelling, be it in text, speech, or music. In this paper, we investigate the predictive power of simple ...
Learning and Evaluation Methodologies for Polyphonic Music Sequence Prediction with LSTMs
(Institute of Electrical and Electronics Engineers, 2020)
Music language models (MLMs) play an important role for various music signal and symbolic music processing tasks, such as music generation, symbolic music classification, or automatic music transcription (AMT). In this ...
Musical Features for Automatic Music Transcription Evaluation
(Transactions of the International Society for Music Information Retrieval (TISMIR, 2021)
This technical report gives a detailed, formal description of the features introduced in the paper: Adrien Ycart, Lele Liu, Emmanouil Benetos and Marcus T. Pearce. "Investigating the Perceptual Validity of Evaluation Metrics ...
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. ...
Investigating the Perceptual Validity of Evaluation Metrics for Automatic Piano Music Transcription
(Ubiquity Press, 2020)
Automatic Music Transcription (AMT) is usually evaluated using low-level criteria, typically by counting the numbers of errors, with equal weighting. Yet, some errors (e.g. out-of-key notes) are more salient than others. ...
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 ...