Tag Archives: music information retrieval

TISMIR Journal Launch and Call for Papers

I am blogging some news related to a project I have been recently contributing.

It brings us great pleasure to announce the launch of the first issue of TISMIR, the Transactions of the International Society for Music Information Retrievalhttps://transactions.ismir.net/

TISMIR was established to complement the widely cited ISMIR conference proceedings and provide a vehicle for the dissemination of the highest quality and most substantial scientific research in MIR. TISMIR retains the Open Access model of the ISMIR Conference proceedings, providing rapid access, free of charge, to all journal content. In order to encourage reproducibility of the published research papers, we provide facilities for archiving the software and data used in the research. The TISMIR publication model avoids excessive cost to the authors or their institutions, with article charges being less than the ISMIR Conference registration fee.

The first issue contains an editorial introducing the journal, four research papers and one dataset paper:

Editorial: Introducing the Transactions of the International Society for Music Information Retrieval – Simon Dixon,  Emilia Gómez,  Anja Volk

Multimodal Deep Learning for Music Genre Classification – Sergio Oramas,  Francesco Barbieri,  Oriol Nieto,  Xavier Serra

Learning Audio–Sheet Music Correspondences for Cross-Modal Retrieval and Piece Identification – Matthias Dorfer,  Jan Hajič jr.,  Andreas Arzt,  Harald Frostel,  Gerhard Widmer

A New Curated Corpus of Historical Electronic Music: Collation, Data and Research Findings – Nick Collins,  Peter Manning,  Simone Tarsitani

A Case for Reproducibility in MIR: Replication of ‘A Highly Robust Audio Fingerprinting System’ – Joren Six,  Federica Bressan,  Marc Leman

Pop Music Highlighter: Marking the Emotion Keypoints – Yu-Siang Huang,  Szu-Yu Chou,  Yi-Hsuan Yang

Two more papers (one research paper and one overview paper) are in press.

Authors:  We look forward to receiving new submissions to the journal – please see the Call for Papers below.

Best Regards
Simon Dixon, Anja Volk and Emilia Gómez

Editors-in-chief, TISMIR

CALL FOR PAPERS

The ISMIR Board is happy to announce the launch of the Transactions of the International Society for Music Information Retrieval (TISMIR), the open-access journal of our community.

 

TISMIR (http://tismir.ismir.net) publishes novel scientific research in the field of Music Information Retrieval (MIR), an interdisciplinary research area concerned with processing, analysing, organising and accessing music information. We welcome submissions from a wide range of disciplines, including computer science, musicology, cognitive science, library & information science, machine learning, and electrical engineering.

 

TISMIR is established to complement the widely cited ISMIR conference proceedings and provide a vehicle for the dissemination of the highest quality and most substantial scientific research in MIR. TISMIR retains the Open Access model of the ISMIR Conference proceedings, providing rapid access, free of charge, to all journal content. In order to encourage reproducibility of the published research papers, we provide facilities for archiving the software and data used in the research. TISMIR is published in electronic-only format, making it possible to offer very low publication costs to authors’ institutions, while ensuring fully open access content. With this call for papers we invite submissions for the following article types:

Article types

Research articles must describe the outcomes and application of unpublished original research. These should make a substantial contribution to knowledge and understanding in the subject matter and should be supported by relevant experiments.

Overview articles should focus in detail on specific aspects of MIR research. Overview articles will provide a comprehensive review of a broad MIR research problem, a critical evaluation of proposed techniques and/or an analysis of challenges for future research. Papers should critically engage with the relevant body of extant literature.

Datasets should present novel efforts in data gathering and annotation that have a strong potential impact in the way MIR technologies are exploited and evaluated.

 

If the paper extends or combines the authors’ previously published research, it is expected that there is a significant novel contribution in the submission (as a rule of thumb, we would expect at  least 50% of the underlying work – the ideas, concepts, methods, results, analysis and discussion – to be new). In addition, if there is any overlapping textual material, it should be rewritten.

 

Review process

The journal operates a double-blind peer review process.  Review criteria include originality, consideration of previous work, methodology, clarity and reproducibility.

 

Publication frequency

The journal is published online as a continuous volume and issue throughout the year, following an open access policy. Articles are made available as soon as they are ready to ensure that there are no unnecessary delays in getting content publicly available.

 

Editorial team

Editors in Chief

Simon Dixon, School of Electronic Engineering and Computer Science, Queen Mary University of London, United Kingdom

Emilia Gómez, Music Technology Group, Universitat Pompeu Fabra, Barcelona, Spain

Anja Volk, Department of Information and Computing Sciences, Utrecht University, Netherlands

Editorial Board

Juan P. Bello, Department of Music and Performing Arts Professions, & Department of Electrical and Computer Engineering, New York University, United States

Arthur Flexer, Austrian Research Institute for Artificial Intelligence (OFAI), Austria

Fabien Gouyon, Pandora, United States

Xiao Hu, Faculty of Education, Division of Information & Technology Studies, University of Hong Kong

Olivier Lartillot, Department of Musicology, University of Oslo, Norway

Jin Ha Lee, Information School, University of Washington, United States

Meinard Mueller, International Audio Laboratories Erlangen, Germany

Geoffroy Peeters, Sound Analysis/Synthesis Team, UMR STMS IRCAM CNRS, France

Markus Schedl, Department of Computational Perception, Johannes Kepler University Linz, Austria

 

Reviewers: The editorial board counts on reviewers from the ISMIR community, who are crucial to the success of the journal. To become a reviewer, please register here http://tismir.ubiquitypress.com/author/register/reviewer/

Journal Manager

Tim Wakeford, Ubiquity Press, United Kingdom

Contact

tismir@ismir.net

 

Website

http://tismir.ismir.net/

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Keynote speech @ 2018 Joint Workshop on Machine Learning for Music – ICML

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I am honored to be keynote speaker at a joint workshop on Machine Learning for Music that will take place this summer in Stockholm. I spent part of my PhD in KTH in Stockholm and it became one of my favourite places, so it is always great to visit. T

In my keynote, I presented some current research of our lab on the analysis and synthesis of singing. In particular, we summarized some recent advances on a set of tasks related to the processing of singing using state-of-the-art deep learning techniques. We discussed their achievements in terms of accuracy and sound quality, and the current challenges, such as availability of data and computing resources. We also discussed the impact that these advances do and will have on listeners and singers when they are integrated in commercial applications.

There is paper related to this research which can be found in arxiv.

 

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Interview at ACM SIGMM Records and the need for interdisciplinary research

The March Issue (Vol.10, Issue 1) of ACM SIGMM Records (News for the Multimedia Community) is out and it includes an interview of myself for the interdisciplinary column, kindly chaired by Cynthia Liem and Jochen Huber.

It is awesome already that there is an interdisciplinary column at SIGMM, recognising the challenges and also the potential of interdisciplinary research and insights as a way to have a comprehensive understanding, in this case, of multimedia computing. I was very pleased to ask questions about my experience in the MIR field and about diversity and interdisciplinarity.

You can read the interview and other interesting content here.

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

I am happy to announce that the International Society for Music Information Retrieval 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.

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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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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¿Pueden los hombres diseñar tecnologías relevantes para las mujeres? El ejemplo en las aplicaciones para la música

Justo antes de vacaciones tuve la oportunidad de escribir un post informal sobre el tema de género gracias a la invitación de MujerTekSpace, un proyecto liderado de la Universidad de Deusto donde se intenta mejorar la visibilidad de la mujer en la ingeniería.

Aquí podéis leer el post publicado, pero lo copio a continuación en su versión extensa, ya que empecé a escribir y se me hizo demasiado largo…

……..—-…….

Desde hace algún tiempo veo a más y más personas preocupadas porque hay pocas mujeres en ingeniería: hay pocas ya en los primeros cursos de la carrera y van quedando menos que hagan el doctorado o lleguen a lo alto de la pirámide profesional (altos cargos directivos o catedráticas). Yo personalmente me he convertido poco a poco en una acérrima defensora de la mujer en la ingeniería, en particular en la investigación y el desarrollo tecnológico.

Mi preocupación fundamental es la siguiente: ¿Cómo será el mundo del futuro si las tecnologías que utilizaremos son investigadas, desarrolladas y evaluadas mayoritariamente por hombres?

Como ejemplo pongamos mi comunidad de investigación: la International Society for Music Information Retrieval (www.ismir.net) (sociedad internacional para la recuperación de la información musical), la cual tengo el honor de presidir (primera presidenta electa por cuestiones estadísticas, como luego verán), formada por investigadores de todo el mundo. Nuestra comunidad está relacionada con compañías punteras hoy en día como shazam, spotify, iTunes, soundcloud (https://soundcloud.com/), deezer (http://www.deezer.com/) BMAT o pandora (¡no las pulseras sino la radio por internet!), empresas que configuran el panorama comercial en sistemas de recomendación de música. Seguro que tienen algunas de éstas aplicaciones en sus ordenadores o teléfonos móviles.

Un estudio que se presentará éste Agosto en la conferencia de Nueva York, y que ha sido liderado por Xiao Hu, investigadora de la Universidad de Hong Kong (Hu et al. 2016), constata la desigual distribución por género (14.7% mujeres vs 85.3%) de autores de artículos científicos a lo largo de los años. De hecho son muy pocas mujeres las que presentan oralmente en la conferencia, y en los últimos 3 años todas las ponencias invitadas las han dado hombres.

1

Además, tanto en nuestro proyecto de mentorías para mujeres como en el panel industrial de la conferencia, hemos podido constatar que la proporción de mujeres es incluso menor en la industria que en la investigación, posiblemente dado que las condiciones laborales son más favorables para la conciliación. Esto parece confirmar que las pocas mujeres que hay se dedican a una investigación que está menos en contacto con el producto.

En el lado positivo, éste estudio refiere que las mujeres más productivas lo son igual que los hombres, que las tendencias no varían entre continentes, que las mujeres que están en grupos de investigación grandes tienen más impacto, y que trabajan en entornos más aplicados, aunque lejos de un producto, lo que parece indicar que la interdisciplinariedad puede proporcionar entornos más diversos en la ingeniería.

Con éstos datos, yo diría que podemos afirmar que nuestras aplicaciones musicales están siendo diseñados por el género masculino, con las consecuentes barreras para la mujer, ya que se incorporan inconscientemente decisiones de diseño no equilibradas. ¿Puede ser que por eso éstas tecnologías no son tan atractivas para la mujer? ¿Puede eso explicar en parte por qué las niñas de hoy en día se sienten poco atraídas por el entorno tecnológico?

Supongo que es algo general en otro tipo de aplicaciones (por ejemplo videojuegos, televisión digital, tecnologías del automóvil o revistas online). Imaginemos entonces que en el futuro pase algo como nos ocurre a los zurdos: ¿será el futuro un mundo donde no podrás cortar bien un papel o tendrás dificultades para abrir una lata de conservas, pero en el dominio digital?

Esperemos que podamos poner remedio antes.

Sobre la autora

Emilia Gómez

Soy el típico caso del bicho raro, como casi todas las mujeres de mi ámbito: una de las dos mujeres que eligió dibujo técnico en mi promoción, una minoría en ingeniería de telecomunicaciones, una de las dos mujeres de mi promoción en el máster en Acústica, Procesado de Señal e Informática Musical del IRCAM en Paris, la única doctoranda hasta ahora de mi director de tesis y la única profesora de mi grupo de investigación. También soy la primera mujer presidenta electa de la ISMIR (International Society in Music Information Retrieval), y la primera en muchas otras cosas, no por ser muy buena sino por cuestiones estadísticas. De hecho soy a menudo una mujer dando clase a un grupo de hombres. Y además soy zurda.

Referencia

Hu, X., Choi, K., Lee, J. H., Laplante, A., Hao, Y., Cunningham, S. J., Downie, J. S. (2016). WiMIR: An Informetric Study on Women Authors in ISMIR. In Proceedings of the 17th International Conference on Music Information Retrieval (ISMIR).

 

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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://i0.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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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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