MML 2019
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MML 2019
September 16, 2019


​Programme

9:00-9:10 Welcome and opening remarks

9:10-10:30 Oral Session 1
Chair: Rafael Ramirez


Cross-Version Singing Voice Detection in Opera Recordings: Challenges for Supervised Learning
Stylianos I. Mimilakis, Christof Weiss, Vlora Arifi-Müller, Jakob Abeßer and Meinard Müller   

Neural Symbolic Music Genre Transfer Insights 
Gino Brunner, Mazda Moayeri, Oliver Richter, Roger Wattenhofer and Chi Zhang
   
Familiar feelings: Listener-rated familiarity in music emotion recognition   

Lloyd May and Michael Casey
 
10:30-10:45 Coffee break

10:45-12:00 Oral Session 2
Chair: Darrell Conklin


Rhythm, Chord and Melody Generation for Lead Sheets using Recurrent Neural Networks 
Cedric De Boom, Stephanie Van Laere, Tim Verbelen and Bart Dhoedt 
   
Bacher than Bach? On Musicologically Informed Artificial Bach Chorale Harmonization
Alexander Leemhuis, Simon Waloschek and Aristotelis Hadjakos

 
Adaptively learning to recognize symbols in handwritten early music 
Luisa Micó, Jose Oncina and José M. Iñesta   

12:00-12:40 Poster Craze (5min per craze)
Chair: Jose Manuel Inesta


Feature-based Classification of Electric Guitar Types    
Renato de Castro Rabelo Profeta and Gerald Schuller

RecurSIA-RRT: Recursive translatable point-set pattern discovery with removal of redundant translators 
David Meredith

Bow Gesture Recognition to Identify Expertise Levels: A Machine Learning Approach    
David Cabrera Dalmazzo and Rafael Ramirez

Symbolic music classification based on multiple sequential patterns    
Kerstin Neubarth and Darrell Conklin

OPTISIA: An Evolutionary Approach to Parameter Optimisation in a Family of Point-Set Pattern-Discovery Algorithms    

Viktor Schmuck and David Meredith

Predicting dynamics in violin pieces with features from melodic motifs
Fabio Jose Muneratti Ortega, Alfonso Perez-Carrillo and Rafael Ramirez

Sequence generation using unwords
​Darrell Conklin

12:40-14:00 Lunch

14:00-15:00 Poster Session 


15:00-15:20 Coffee break


15:20-16:35 Oral Session 3: 
Chair: 
Rafael Ramirez

A Machine Learning Approach to Study Expressive Performance Deviations in Classical Guitar
Sergio Giraldo, Rafael Ramirez, Alberto Nasarre and Isabelle Heroux

Enhanced De-Essing via Neural Networks    
Simon Hestermann and Niklas Deffner

Representation, Exploration and Recommendation of Playlists
Piyush Papreja, Hemanth Venkateswara and Sethuraman Panchanathan

16:35-16:40  Closing remarks

17:30 ECML/PKDD Opening Ceremony and Keynote 
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