Information Extraction from Music Audio Juan Bello , New York University Friday, November 30, 3:30pm Computer Science 105 This talk discusses a mix of concepts, problems and techniques at the crossroads of signal processing, machine learning and music. I will start by motivating the use of content-based methods for the analysis and retrieval of music. Then, I will introduce work in three projects being investigated in my lab: automatic chord recognition using hidden Markov models, music structure analysis using probabilistic latent component analysis, and feature learning using convolutional neural networks. In the process of doing so, I hope to illustrate some of the challenges and opportunities in the field of music informatics. Juan Pablo Bello is an Associate Professor of Music Technology at New York University. In 1998 he received his BEng in Electronics from the Universidad Simón Bolívar in Caracas, Venezuela, and in 2003 he earned a doctorate in Electronic Engineering at Queen Mary, University of London. Juan teaches and researches on the computer-based analysis of musical signals and its applications to music information retrieval, digital audio effects and interactive music systems. He is the principal investigator of the music informatics group of the Music and Audio Research Lab (MARL) at NYU. For more information please visit: https://files.nyu.edu/jb2843/public/ http://marl.smusic.nyu.edu/