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Modeling Analog Dynamic Range Compressors using Deep Learning and State-space Models
We describe a novel approach for developing realistic digital models of dynamic range compressors for digital audio production by analyzing their analog prototypes.
Online Active Learning For Sound Event Detection
Online Active Learning (OAL) is a paradigm that addresses this issue by simultaneously minimizing the amount of annotation required to train a classifier and adapting to changes in the data over the duration of the data collection process.
Learnable Front Ends Based on Temporal Modulation for Music Tagging
While end-to-end systems are becoming popular in auditory signal processing including automatic music tagging, models using raw audio as input needs a large amount of data and computational resources without domain knowledge.
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