Send the link below via email or IMCopy
Present to your audienceStart remote presentation
- Invited audience members will follow you as you navigate and present
- People invited to a presentation do not need a Prezi account
- This link expires 10 minutes after you close the presentation
- A maximum of 30 users can follow your presentation
- Learn more about this feature in our knowledge base article
Do you really want to delete this prezi?
Neither you, nor the coeditors you shared it with will be able to recover it again.
Make your likes visible on Facebook?
You can change this under Settings & Account at any time.
Music & Machine Learning
Transcript of Music & Machine Learning
Engineering HCI Music
Retrieval History Research information retrieval feature extraction machine learning time-series analysis signal processing MIR music
systems What Do We Do? Expressive Analysis expressivity methodology results discussion what is ? how do we define expressivity? feature extraction onset detection Bello JP, Daudet L, Abdallah S, Duxbury C, Davies M, et al. (2005) A tutorial on onset detection in music signals. IEEE Trans on Speech and Audio Processing 13: 1035–1047. pitch energy onset Particle Swarm Optimization 93.3% PSO + Peak PSO + Peak Onset Deviation Onset Deviations Data Set so what? B.Sc - Computer Engineering M.A - Sound Engineering and Design M.Sc - Sound and Music Computing Phd. Information and Communication Technologies Tan Özaslan Xavier Serra Information Retrieval Machine Learning Feature Extraction now What I am going to talk about... Musical Expressivity rough data analysis Data Analysis outcomes thank you - Future composers performers Recommender Systems Data Analysis machine learning Machine Learning f-fold cross validation solution test classification Note Onset Deviations as Musical Piece Signatures Note Onset Deviations as Performer Signatures Data Analysis Computer Programming Algorithms Mobile Programming (Android) Data Analysis with
Matlab - R Music Information Retrieval Music Technologies Teaching Signal Analysis
(Audio) Data Analysis Applications David Cope