Seminar at Unviversidad Carlos III de Madrid

I'll be giving a seminar for PhD students at the Department of Computer Science (Research Group SCALAB) of the University Carlos III de Madrid next Friday. The topic will be on how to combine music and operations research. From their website:

Title: Music and operations research: applications in automatic generation music and dance hit prediction.

Presenter: Dorien Herremans (Queen Mary University)

Date: November 27, 2015

Time: 4:30 pm - 6:30 pm

Organizer: Department of Computer Science - Research Group SCALAB

Place: Sabatini Building 2.1.C19 (Leganés Campus)

ECTS: 0.3

The field of operations research offers us powerful optimization and data mining techniques. In This talk we'll explore how These can be useful in the domain of music by looking at two applications: automatic generation and dance music hit prediction.

In the first part of the talk, we'll look at generating music as an optimization problem. In particularly, we'll be focusing on music Which has a long term structure. A Variable Neighbourhood powerful search algorithm (VNS) was developed, Which is Able to generate a range of musical styles based on it's objective function, constraining Whilst the music to a structural template. In the first stage of the project, an objective function based on rules from music theory was used to generate counterpoint. In the next stage, a machine learning approach is combined With the VNS in order to generate structured music for the bagana, an Ethiopian lyre. The approach Followed In This research Allows us to combine the power of machine learning methods With optimization algorithms.

In the second part of this talk, we'll zoom in on the dance hit song prediction problem. With annual investments of several billions of dollars worldwide, record companies can benefit tremendously by gaining insight into what Actually Makes a hit song. We'll describe how we built a database of dance hit songs from 1985 Until 2013, Which includes basic musical features, as well as more advanced features to capture That temporal aspect. Different classifiers: such as SVM and logistic regression are used to build and test prediction models dance hit. The RESULTING model has a good performance Whether predicting When a song is a "top 10" dance hit versus a lower position listed.

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