We develop a large number of software tools and hosting infrastructures to support the research developed at the Department. We will be detailing in this section the different tools available. You can take a look for the moment at the offer available within the UPF Knowledge Portal, the innovations created in the context of EU projects in the Innovation Radar and the software sections of some of our research groups:

 

 Artificial Intelligence

 Nonlinear Time Series Analysis

 Web Research 

 

 Music Technology

 Interactive  Technologies

 Barcelona MedTech

 Natural Language  Processing

 Nonlinear Time Series  Analysis

UbicaLab

Wireless Networking

Educational Technologies

GitHub

 

 

Back Bosch J.J., Bittner R.M., Salamon J., Gómez E. A Comparison of Melody Extraction Methods Based on Source-Filter Modelling. Proc. 17th International Society for Music Information Retrieval Conference (ISMIR 2016)

Bosch J.J., Bittner R.M., Salamon J., Gómez E. A Comparison of Melody Extraction Methods Based on Source-Filter Modelling. Proc. 17th International Society for Music Information Retrieval Conference (ISMIR 2016)

 

This work explores the use of source-filter models for pitch  salience estimation and their combination with different pitch tracking and voicing estimation methods for automatic melody extraction. Source-filter models are used to create a mid-level representation of pitch that implicitly incorporates timbre information. The spectrogram of a musical audio signal is modelled as the sum of the leading voice produced by human voice or pitched musical instruments) and accompaniment. The leading voice is then modelled with a Smoothed Instantaneous Mixture Model (SIMM) based on a source-filter model. The main advantage of such a pitch salience function is that it enhances the leading voice even without explicitly separating it from the rest of the signal. We show that this is beneficial for melody extraction, increasing pitch estimation accuracy and reducing octave errors in comparison with simpler pitch salience functions. The adequate combination with voicing detection techniques based on pitch contour characterisation leads to significant improvements over state-of-the-art methods, for both vocal and instrumental music.

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