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An End-to-End Neural Network for Polyphonic Music Transcription
(arxiv, 2015-08)
We present a neural network model for polyphonic music transcription. The architecture of the proposed model is analogous to speech recognition systems and comprises an acoustic model and a music language mode}. The acoustic ...
Modeling plate and spring reverberation using a DSP-informed deep neural network
Plate and spring reverberators are electromechanical systems first used and researched as means to substitute real room reverberation. Nowadays they are often used in music production for aesthetic reasons due to their ...
End-to-End Probabilistic Inference for Nonstationary Audio Analysis
A typical audio signal processing pipeline includes multiple disjoint analysis stages, including calculation of a time-frequency representation followed by spectrogram-based feature analysis. We show how time-frequency ...
Data-Efficient Weakly Supervised Learning for Low-Resource Audio Event Detection Using Deep Learning
We propose a method to perform audio event detection under the common constraint that only limited training data are available. In training a deep learning system to perform audio event detection, two practical problems ...