News and Events

New session of the MOOC on Audio Signal Processing for Music Applications

A new session of the MOOC on Audio Signal Processing for Music Applications is starting in Coursera on September 26th. To enrol go to

This is a 10 week long course that focuses on the spectral processing techniques of relevance for the description and transformation of sounds, developing the basic theoretical and practical knowledge with which to analyze, synthesize, transform and describe audio signals in the context of music applications.

The course is free and based on open software and content. The demonstrations and programming exercises are done using Python under Ubuntu, and the references and materials for the course come from open online repositories. The software and materials developed for the course are also distributed with open licenses.

The course assumes some basic background in mathematics and signal processing. Also, since the assignments are done with the programming language Python, some software programming skills in any language are most helpful. 

23 Sep 2016 - 09:38 | view
Awards from the Board of Trustees of the UPF
Gopala K. Koduri and Sankalp Gulati got the 3rd price of the Knowledge Transfer category given by the Board of Trustees of the UPF for their MusicMuni initiative. MusicMuni will be a spin-off company of the MTG aiming to exploit several technologies developed within the CompMusic project specific for analyzing Indian music in the context of music education. (
Xavier Serra got an award in the category of teaching quality, also given by the Board of Trustees of the UPF, for the Master course on Audio Signal Processing for Music Applications and the accompanying MOOC with the same name. (
19 Sep 2016 - 09:51 | view
Jordi Bonada and Merlijn Blaauw present at Interspeech 2016 and win the Singing Synthesis Challenge
15 Sep 2016 - 10:46 | view
Zacharias Vamvakousis defends his PhD thesis on September 16th
16 Sep 2016
Zacharias Vamvakousis defends his PhD thesis entitled "Digital Musical Instruments for People with Physical Disabilities" on Friday September 16th 2016 at 17:30h in room 55.316 of the Communication Campus of the UPF.

The jury of the defense is: Jose Manuel Iñesta (Alicante University), Hendrik Purwins (Aalborg University), Alfonso Perez (UPF)

Thesis abstract:
Playing a musical instrument has been shown to have a positive impact in the life of individuals in many different ways. Nevertheless, due to physical disabilities, some people are unable to play conventional musical instruments. In this dissertation, we consider different types of physical disabilities and implement specific digital musical instruments suitable for people with disabilities of each type. Firstly, we consider the case of people with limited sensorimotor upper limb functions, and we construct low-cost digital instruments for three different scenarios. Results indicate that the constructed prototypes allow musical expression and improve the quality of life of these users. Secondly, we consider disabilities such as tetraplegia or locked-in syndrome with unaffected eye-movements. For individuals with such conditions, we propose the EyeHarp, a gaze-controlled digital music instrument, and develop specific target selection algorithms which maximize the temporal and spatial accuracy required in music performance. We evaluate the instrument on subjects without physical disabilities, both from an audience and performer perspective. Results indicate that the EyeHarp has a steep learning curve and it allows expressive music performances. Finally, we examine the case of brain-controlled music interfaces. We mainly focus in auditory event related potential-based interfaces. In particular, we investigate and evaluate how timbre, pitch and spatialization auditory cues affect the performance of such interfaces.
15 Sep 2016 - 10:41 | view
Sergio Giraldo defends his PhD thesis on September 16th
16 Sep 2016
Sergio GIraldo defends his PhD thesis entitled "Computational Modelling of Expressive Music Performance in Jazz Guitar: A Machine Learning Approach" on Friday September 16th 2016 at 15:00h in room 55.309 of the Communication Campus of the UPF.

The jury of the defense is: Jose Manuel Iñesta (Alicante University), Hendrik Purwins (Aalborg University), Enric Guaus (UPF)

Thesis abstract:
Computational modelling of expressive music performance deals with the analysis and characterization of performance deviations from the score that a musician may introduce when playing a piece in order to add expression. Most of the work in expressive performance analysis has focused on expressive duration and energy transformations, and has been mainly conducted in the context of classical piano music. However, relatively little work has been dedicated to study expression in popular music where expressive performance involves other kinds of transformations. For instance in jazz mu- sic, ornamentation is an important part of expressive performance but is seldom indicated in the score, i.e. it is up to the interpreter to decide how to ornament a piece based on the melodic, harmonic and rhythmic contexts, as well as on his/her musical background. In this dissertation we investigate the computational modelling of expressive music performance in jazz music, using the guitar as a case study. High-level features are extracted from music scores, and expressive transformations (including timing, energy and ornamentation transformations) are obtained from the corresponding audio recordings. Once each note is characterized by its musical context description and expressive deviations, several machine learning techniques are explored to induce both, black-box and interpretable rule-based predictive models for duration, onset, dynamics and ornamentation transformations. The models are used to both, render expressive performances of new pieces, and attempt to understand expressive performance. We report on the relative importance of the considered music features, quantitatively evaluate the accuracy of the induced models, and discuss some of the learnt expressive performance rules. Furthermore, we present different approaches to semi-automatic data extraction-analysis, as well as some applications in other research fields. The findings, methods, data extracted, and libraries developed for this work are a contribution to expressive music performance field.
15 Sep 2016 - 10:37 | view
Technology Transfer position at the MTG
The Music Technology Group (MTG) of the Universitat Pompeu Fabra, Barcelona ( invites applications for a tech transfer position.
The MTG is a research group specialized in sound and music computing committed to have social impact and with a strong focus on technology transfer activities. The MTG has created several spin-off companies, is active in licensing technologies, collaborates and has contracts with a number of companies, and develops and maintains open software and collaborative based technologies, like Essentia or Freesound, that are exploited in industrial contexts.
Successful candidates for this position should be experienced researchers with a motivation and experience on technology transfer wanting to take a leading role in promoting technology transfer initiatives within the music sector.
Responsible for driving all technology transfer processes to resolution, from market prospection, preparation of internal results for exploitation and the negotiation and follow-up of contracts / license agreements with external customers and the university. Specifically to:
  • Promote the existing technologies and those resulting from our ongoing research projects.
  • Understand the market needs and identify potentially interested partnerships/ customers.
  • Collaborate with the researchers in the preparation of the technologies to be ready for the exploitation.
  • Actively look for tech transfer opportunities.
  • Manage technology transfer relationships (negotiations, licensing agreements).
  • PhD or comparable research experience.
  • Experience in applied research and / or technology transfer activities (at least 1 year).
  • Marketing skills and knowledge of basic business and Intellectual Property topics.
  • Understanding the industrial sectors related to Music Technology.
  • Fluent in English and Spanish.
  • It is desirable that the candidate has worked outside Spain at least 2 years in the last 3 years.

Interested candidates should send a resume as well as a motivation letter, addressed to Xavier Serra, to mtg-info [at] upf [dot] edu (subject: tech%20transfer%20position) before October 15th.

14 Sep 2016 - 15:32 | view
Participation to VSGAMES 2016

Some prototypes were presented at VSGAMES 2016 - 8th International Conference on Virtual Worlds and Games for Serious Applications by Álvaro Sarasúa and Jordi Janer, members of the MIR-lab@MTG.

These games where developed in the context of the PHENICX project and with the goal of interacting with classical music concerts.

Janer, J., Gómez E., Martorell A., Miron M., & de Wit B. (2016). Immersive Orchestras: audio processing for orchestral music VR content. VSGAMES 2016 - 8th International Conference on Virtual Worlds and Games for Serious Applications. Abstract

Sarasúa, Á., Melenhorst M., Julià C. F., & Gómez E. (2016). Becoming the Maestro - A Game to Enhance Curiosity for Classical Music. 8th International Conference on Virtual Worlds and Games for Serious Applications (VS-Games 2016).


12 Sep 2016 - 09:42 | view
Participation to SMC 2016
Olga Slizovskaia, Sertan Şentürk, Rong Gong and Juanjo Bosch will participate to the 13th Sound and Music Computing Conference that takes place in Hamburg from August 31st to September 3rd 2016. They will be presenting the following papers:
29 Aug 2016 - 10:35 | view
Talk on factor analysis for audio classification tasks by Hamid Eghbal-zadeh
1 Aug 2016
On Monday, 1st of August at 15:00h in room 55.410 there will be a talk by Hamid Eghbal-zadeh (Department of Computational Perception, Johannes Kepler University of Linz, Austria) on "A small footprint for audio and music classification".
Abstract: In many audio and music classification tasks, the aim is to provide a low-dimensional representation for audio excerpts with a high discrimination power to be used as excerpt-level features instead of the audio feature sequence. One approach would be to summarize the acoustic features into a statistical representation and use it for classification purposes. A problem of many of the statistical features such as adapted GMMs is that they are very high dimensional and also capture unwanted characteristics about the audio excerpts which does not represent their class. Using Factor Analysis, the dimensionality can be dramatically reduced and the unwanted factors can be discarded from the statistical representations. The state-of-the-art in many speech-related tasks use a specific factor analysis to extract a small footprint from speech audios. This fixed-length low-dimensional representation is known as i-vector. I-vectors are recently imported in MIR and have shown a great promise. Recently, we won the Audio Scene Classification challenge (DCASE-2016) using i-vectors. Also, we will present our noise-robust music artist recognition system via i-vector features at ISMIR-2016.
28 Jul 2016 - 16:00 | view
Large participation of the MTG at ISMIR 2016
16 MTG researchers participate to the 17th International Society for Music Information Retrieval Conference (ISMIR 2016) that takes place in New York from August 7th to the 11th 2016. ISMIR is the world’s leading research forum on processing, searching, organizing and accessing music-related data. MTG's main contributions are the presentations of 11 papers in the main program, 2 tutorials, and 2 papers in the satellite workshop DLFM 2016.
Here are the papers presented as part of the main program:
Here are the tutorials that MTG people are organizing and involved in:
27 Jul 2016 - 10:47 | view