End-to-End Learning for Musical Instruments Classification

• Published in: Conference record - Asilomar Conference on Signals, Systems, & Computers pp. 1607 - 1611
• Main Authors: Profeta, Renato, Schuller, Gerald
• Format: Conference Proceeding
• Language: English
• Published: IEEE 31.10.2021
• Subjects: Convolutional neural networks; deep learning; end-to-end learning; Filter banks; Instruments; Music information retrieval; musical instruments classification; Neural networks; Spectrogram; Timbre

Musical instruments classification is a widely studied topic in Music Information Retrieval (MIR) and Signal Processing. The applications of this subject go from indexing of an audio database, automatic transcription, recommender systems, to music search by timbre, music annotation and others. Many...