Category Archives: research

New open-access journal Transactions of ISMIR, open for submissions

We launched the Transactions of the International Society for Music Information Retrieval, the open access journal of the ISMIR society at Ubiquity press. I am serving as Editor-in-Chief, together with Simon Dixon and Anja Volk.

Transactions of the International Society for Music Information Retrieval

TISMIR publishes novel scientific research in the field of music information retrieval (MIR).

We welcome submissions from a wide range of disciplines: computer science, musicology, cognitive science,  library & information science and electrical engineering.

We currently accept submissions.

View our submission guidelines for more information.

TISMIR

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Special Issue at IEEE Multimedia Magazine

I have been collaborating for a while now on the edition of a Special Issue at IEEE Multimedia Magazine, which gathers state-of-the-art research on multimedia methods and technologies aimed at enriching music performance, production and consumption.

I have had the change to co-edit this issue with my colleagues Cynthia Liem (TU Delft, The Netherlands) and George Tzanetakis (University of Victoria, Canada), and I am very happy with the outcomes.

It is the second time I act as a co-editor for a journal (the first one was at JNMR and related to computational ethnomusicology) and I learnt a lot from the process. Editors have to asure good submissions, good reviews and recommendations, keeping the coherence and theme that we wanted to give as a message to our community. Yes: access, distribution and experiences in music are changing with new technologies. I am very happy with the outcomes!  Check our editorial paper here, and the full issue here.

And I love the design!

Captura de pantalla 2017-03-01 a las 10.45.27.png

 

 

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Journal paper and open dataset for source separation in Orchestra music

As part of the PHENICX project, we have recently published our research results in the task of audio sound source separation, which is the main research topic of one of our PhD students, Marius Miron.

During this work, we developed a method for orchestral music source separation along with a new dataset: the PHENICX-Anechoic dataset. The methods were integrated into the  PHENICX project for tasks as orchestra focus/instrument enhancement. To our knowledge, this is the first time source separation is objectively evaluated in such a complex scenario. 

This is the complete reference to the paper:

M. Miron, J. Carabias-Orti, J. J. Bosch, E. Gómez and J. Janer, “Score-informed source separation for multi-channel orchestral recordings”, Journal of Electrical and Computer Engineering (2016))”

Abstract: This paper proposes a system for score-informed audio source separation for multichannel orchestral recordings. The orchestral music repertoire relies on the existence of scores. Thus, a reliable separation requires a good alignment of the score with the audio of the performance. To that extent, automatic score alignment methods are reliable when allowing a tolerance window around the actual onset and offset. Moreover, several factors increase the difficulty of our task: a high reverberant image, large ensembles having rich polyphony, and a large variety of instruments recorded within a distant-microphone setup. To solve these problems, we design context-specific methods such as the refinement of score-following output in order to obtain a more precise alignment. Moreover, we extend a close-microphone separation framework to deal with the distant-microphone orchestral recordings. Then, we propose the first open evaluation dataset in this musical context, including annotations of the notes played by multiple instruments from an orchestral ensemble. The evaluation aims at analyzing the interactions of important parts of the separation framework on the quality of separation. Results show that we are able to align the original score with the audio of the performance and separate the sources corresponding to the instrument sections.

The PHENICX-Anechoic dataset includes audio and annotations useful for different MIR tasks as score-informed source separation, score following, multi-pitch estimation, transcription or instrument detection, in the context of symphonic music. This dataset is based on the anechoic recordings described in this paper:

Pätynen, J., Pulkki, V., and Lokki, T., “Anechoic recording system for symphony orchestra,” Acta Acustica united with Acustica, vol. 94, nr. 6, pp. 856-865, November/December 2008.

For more information about the dataset and how to download you can access the PHENICX-Anechoic web page.

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New project on MIR & singing: CASAS

At my lab we are starting a new project where we integrate our expertise in singing voice processing and music information retrieval to generate tools for choir singers.

CASAS (Community-Assisted Singing Analysis and Synthesis) is a project funded by the Ministry of Economy and Competitiveness of the Spanish Government (TIN2015-70816-R), that started in  January 1st 2016 and will end in December 31st 2018.

https://i2.wp.com/mtg.upf.edu/system/files/imagecache/projects_tech_thumbs/projects/Logo.jpgHumans use singing to create identity, express emotion, tell stories, exercise creativity, and connect with each other while singing together. This is demonstrated by the large community of music singers active in choirs and the fact that vocal music makes up an important part of our cultural heritage. Currently, an increasing amount of music resources are becoming digital, and the Web has become an important tool for singers to discover and study music, as a feedback resource and as a way to share their singing performances. The CASAS project has two complementary goals:

  • The first one is to improve state-of-the-art technologies that assist singers in their musical practice. We research on algorithms for singing analysis and synthesis (ex: automatic transcription, description, synthesis, classification and visualization), following a user-centered perspective, and with the goal of making them more robust, scalable and musically meaningful.
  • The second one is to enhance current public-domain vocal music archives and create research data for our target music information retrieval (MIR) tasks. Our project put a special emphasis on choral repertoire in Catalan and Spanish.

We exploit our current methods for Music Information Retrieval and Singing Voice Processing, and we involve a community of singers that use our technologies and provide their evaluations, ground truth data and relevance feedback.

I did my first logo, which is inspired by choirs, audio & “houses”, which is the english translation of “casas”. It will be an amazing project!

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Paper on melodic similarity in flamenco now online

Our paper on melodic similarity is finally online! The paper is titled

Melodic Contour and Mid-Level Global Features Applied to the Analysis of Flamenco Cantes

This work focuses on the topic of melodic characterization and similarity in a specific musical repertoire: a cappella flamenco singing, more specifically in debla and martinete styles. We propose the combination of manual and automatic description. First, we use a state-of-the-art automatic transcription method to account for general melodic similarity from music recordings. Second, we define a specific set of representative mid-level melodic features, which are manually labelled by flamenco experts. Both approaches are then contrasted and combined into a global similarity measure. This similarity measure is assessed by inspecting the clusters obtained through phylogenetic algorithms and by relating similarity to categorization in terms of style. Finally, we discuss the advantage of combining automatic and expert annotations as well as the need to include repertoire-specific descriptions for meaningful melodic characterization in traditional music collections.

This is the result of a joint work of the COFLA group, where I am contributing with tecnologies for the automatic transcription and melody description of music recordings.

This is an example on how we compare flamenco tonás using melodic similarity and phylogenetic trees:

nnmr_a_1174717_f0007_b

And this is a video example of the type of styles we analyze in this paper, done by Nadine Kroher based on her work at the MTG:

You can read the full paper online:

http://www.tandfonline.com/doi/full/10.1080/09298215.2016.1174717

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Looking for a smart PhD student for next year

The Music Technology Group (MTG) of the Department of Information and Communication Technologies, Universitat Pompeu Fabra in Barcelona is opening a PhD fellowship in the area of Music Information Retrieval to start in the Fall of 2016.

Application closing date: 05/05/2016

Start date: 01/10/2016

Research lab:  Music Information Research lab, Music Technology Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra
Supervisor: Emilia Gómez

Duration: 3+1 years

Topics: automatic transcription, sound source separation, music classification, singing voice processing, melody extraction, music synchronization, classical music, computational ethnomusicology.

Requirements: Candidates must have a good Master Degree in Computer Science, Electronic Engineering, Physics or Mathematics. Candidates must be confident in some of these areas: signal processing, information retrieval, machine learning, have excellent programming skills, be fluent in English and possess good communication skills. Musical knowledge would be an advantage, as would previous experience in research and a track record of publications.

More information on grant details:
http://portal.upf.edu/web/etic/doctorat
http://portal.upf.edu/web/etic/predoctoral-research-contracts
Provisional starting date: October 1st 2016

Application: Interested candidates should send a motivation letter, a CV (preferably with references), and academic transcripts to Prof. Emilia Gómez (emilia.gomez@upf.edu) before May 1st 2016. Please include in the subject [PhD MIR].

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CANTE: Open Algorithm, Code & Data for the Automatic Transcription of Flamenco Singing

Over the last months, several journal publications related to our research on flamenco & technology are finally online.

One of them is a work with my former PhD student, Nadine Kroher (who now moved to Universidad de Sevilla), on the automatic transcription of flamenco singing. Flamenco singing is really challenging in terms of computational modelling, given its ornamented character and variety, and we have designed a system for its automatic transcription, focusing on polyphonic recordings.

flamencoTranscriptionKroherGomez

The proposed system outperforms state of the art singing transcription systems with respect to voicing accuracy, onset detection, and overall performance when evaluated on flamenco singing datasets. We hope it think will be a contribution not only to flamenco research but to other singing styles.

You can read about our algorithm at the paper we published at IEEE TASP, where we present the method, strategies for evaluation and comparison with state of the art approaches. You can not only read, but actually try it, as we published an open source software for the algorithm, plus a music dataset for its comparative evaluation, cante2midi (I will talk about flamenco corpus in another post). All of this to foster research reproducibility and motivate people to work on flamenco music.

¡Olé!

 

 

 

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FAST project: Acoustic and semantic technologies for intelligent music production and consumption

Yesterday I arrived from Paris, where I attended, as Advisory Board member, a meeting of the FAST Project (www.semanticaudio.ac.uk).

FAST-IMPACT stands for “Fusing Acoustic and Semantic Technologies for Intelligent Music Production and Consumption” and it is funded by EPRSC, Engineering and Physical Sciences Research Countil, UK with 5,199,944 £ (side note: OMG this is real funding, they should know at the new Spanish Agencia Estatal para la Investigación)

According to their web site, This five-year EPSRC project brings the very latest technologies to bear on the entire recorded music industry, end-to-end, producer to consumer, making the production process more fruitful, the consumption process more engaging, and the delivery and intermediation more automated and robust. It addresses three main premises:

(i) that Semantic Web technologies should be deployed throughout the content value chain from producer to consumer;

(ii) that advanced signal processing should be employed in the content production phases to extract “pure” features of perceptual significance and represent these in standard vocabularies;

(iii) that this combination of semantic technologies and content-derived metadata leads to advantages (and new products and services) at many points in the value chain, from recording studio to end-user (listener) devices and applications.

The project is leaded by Dr Mark Sandler, Queen Mary University of London, and include as project participants University of Nottingham (leaded by Dr. Steve Benford), University of Oxford (leaded by Dr. David Deroure), Abbey Road Studios, BBC R&D, The Internet Archives, Microsoft Research and Audiolaboratories Eerlangen.

The results for this first year are amazing, as it can bee seen on the web, in terms of publication, scientific and technological outcomes but more important, great and inspiring ideas!

I am honoured to be part of the advisory board with such excellent researchers and contribute to the Project as much as I can. Some photos of the meeting:

 

 

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CfP: Multimedia Technologies for Enriched Music Performance, Production, and Consumption

Publication: Jan. Mar. 2017
Submission deadline: Feb. 1st 2016

Screen Shot 2015-12-03 at 11.50.49

I am co-editing, together with my colleagues Cynthia Liem and George Tzanetakis,  a special issue on IEEE Multimedia related to music.

Internet access, mobile devices, social networks, and automated multimedia technologies enabling sophisticated information analysis and access have radically changed the ways in which people find entertainment, discover new interests, and generally express themselves online — seemingly without any physical or social barriers. Thanks to the increasing affordability of sensing, storage, and sharing, we note that information takes increasingly rich and hybrid multimedia forms, in which multimodal information streams co-occur in various social consumption settings.

This phenomenon also has enabled opportunities in the music domain. In music performance, novel opportunities for expression are found, exploiting (live) analysis and novel interaction mechanisms with musical data in multiple modalities. In music production, sophisticated multimedia data analysis techniques can both lead to more efficient and scalable workflows, as well as richer and better interfaces. In music consumption, the music data richness and its contextual and social embedding lead to novel consumer experiences stimulating music appreciation. Concerts turn into multimodal, multiperspective, and multilayer digital artifacts that can be easily explored, customized, personalized, (re)enjoyed and shared among various types of users; similar notions and opportunities hold for the consumption of general music recordings.

The goal of this special Issue is to gather state-of-the-art research on multimedia methods and technologies aimed at enriching music performance, production and consumption. We solicit novel, original work that is not published or under review elsewhere.

Topics of interest include, but are not limited to:

  • Processing of multimodal music data streams (e.g. audio, video, images, score, text, gesture…) for music performance, production and/or consumption
  • Multimedia content description and indexing for music performance, production and/or consumption
  • Multimedia information retrieval methods for music performance, production and/or consumption
  • Novel interaction mechanisms for music performance, production and/or consumption
  • Novel user interfaces for music performance, production and/or consumption
  • Novel user experience paradigms for music performance, production and/or consumption
  • Social networking and sharing for music performance, production and/or consumption
  • Digital mechanisms for remote music performers and audiences
  • Active listening, audience immersion, and inclusion of new music audiences
  • User-awareness, personalization and intent in music performance, production and/or consumption
  • Context-awareness and automatic context adaptation in music performance, production and/or consumption

Submission Guidelines

See www.computer.org/web/peer-review/magazines. Submissions should not exceed 6,500 words, with each table and figure counting for 200 words. Manuscripts should be submitted electronically (https://mc.manuscriptcentral.com/mm-cs), selecting this special issue option.

Guest Editors

Detailed call for papers

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Music Information Retrieval & Flamenco: Experiment on note segmentation

Current experiment (updated October 2015)

We are running an experiment on note segmentation in flamenco, in order to understand the mechanisms behind manual transcriptions and improve our automatic transcription methods.

You can help by doing this exercise where you will have to segment 10 short flamenco excerpts into notes (it requires less than 1 hour of your time), and you will have the chance to listen in detail to some flamenco singing.

About

My current research in music information retrieval also addresses flamenco music, specially flamenco singing. I am interested to understand and model with computing tools the way humans transcribe flamenco music in order to generate automatic transcriptions of flamenco performances. Transcriptions are useful for musical analysis in terms of scale, patterns and style. More info on the context of my research can be found at the COFLA web site.

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