Tag Archives: mir

TONAS: a new dataset of flamenco a cappella sung melodies with corresponding manual transcriptions

 

Some weeks ago we announced the release of a new dataset of flamenco singing: TONAS

The dataset includes 72 sung excerpts representative of three a cappella flamenco singing styles, i.e. Tonás (Debla and two variants of Martinete), together with manually corrected fundamental frequency and note transcriptions.

This collection was built by the COFLA team in the context of our research project for melodic transcription, similarity and style classification in flamenco music.

Further information about the music collection, how the samples were transcribed and by who, is available on the dataset website, where you can of course download the audio, metadata and transcription files.

We hope that this collection will be useful, whether for automatic transcription of the singing voice or any other research topic (e.g. pitch estimation, onset detection, melodic similarity, singer identification, style classification), and we hope this dataset will increase the interest of our scientific community on the particular challenges of flamenco singing.

For the moment we got quite a number of downloads for different purposes: research on music transcription, onset detection, folk music, personal study of singing techniques, and even for curiosity! 🙂

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Teaching Music Information Retrieval: courses, resources and funding!

 

I proposed a session on teaching Music Information Retrieval at ISMIR in Porto last week, as part as its Demo/Late-break session. As a result of this session, we decided to create a site to centralize teaching resources related to Music Information Retrieval. It is addressed to teachers and students interested on these technologies from an educational point of view. Current resources include:

  • List of courses: list of courses related to MIR in different levels, institutions and countries.
  • Educational resources: collaborative list of small teaching material: exercises, musical examples, code.

I am very happy because of the great contribution by the community so far. There are many course already there (I think most of them!) and few great education resources. I hope it’s just the start!

In terms of funding, UPF’s teaching innovation services (plaQUID) got interested, and I got some funding to have a larger impact of MIR & teaching in our local context.

emilia

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ISMIR 2012

Last week I attended my favorite conference, the International Society of Music Information Retrieval Conference. It took place in Porto, Portugal. I gave a presentation on our flamenco project. If you are interested, these are the slides.

It was a very intense conference, where I attended very nice presentations and I got many great ideas for future research. I specially enjoyed the last-minute demo session, which was something different to what I am used to.

Now, back to work!

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International Classical Music Award for Classical Planet

One of the projects I’ve been involved on got a great award. Congratulations to FIA!!

I quote here some information:

“The renowned Polish composer Krzysztof Penderecki wins the Lifetime Achievement Award; French pianist Jean-Efflam Bavouzet is Artist of the Year; German pianist Joseph Moog Young Artist of the Year; Ondine Label of the Year. A Special Achievement Award goes to the producer and re-recording engineer Ward Marston. The Classical Website Award goes to ‘classicalplanet.com’, an outstanding project coordinated by the Fundación Albéniz and offering musical content as well as a social networking platform for young musicians. Among the recipients of the Awards in the 14 CD and DVD, the Jury selected the ECM recording of piano works by Robert Schumann played by Andras Schiff  as Recording of the Year.”

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Book on Multimodal Music Processing

I’m very happy to have coauthored a chapter in this book on Multimodal Music Processing, as a result of a seminar that Meinard Muëller, Masataka Goto and Simon Dixon organized last year.

I contributed to a chapter about user modeling and personalization, which I think it’s a key aspect of future MIR systems. Searches, descriptors, similarity measures and classification algorithms should be adapted to different user needs, in order to provide powerful and informative services of recommendation and retrieval.

I hope you will find it interesting!

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Multimodality, Music Processing and Flamenco Research

This week, I am attending a focused seminar in Multimodal Music Processing.  The organizers managed to gather together an amazing group of researchers from different areas in music technology. We are trying to discuss on the challenges related to the combination of different modalities of information into music processing systems.

What do we mean by multi-modality?

A “Modality” can be defined as “any of the various types of sensation, such as vision or hearing” or even “any of the five senses”. How to take advantage of information from our five senses into music processing systems? If we also consider the “context” and the “user” as an information source, we then have a huge amount of information to be efficiently combined.

This is mainly the challenge of all of the area, dealing and combining data and information for a particular task.

I tried to apply multimodality to my current project in flamenco music and I realized we are facing a multi-modal, multi-disciplinary and multi-cultural problem.

–       Multi-modal: we are dealing with the integration of different knowledge sources: music, expression, context, cultural information, anthropological data, listener judgments, text, image and movement.

–       Multi-disciplinary: each modality formalizes differently, so how to formalize knowledge from other disciplines into music processing systems: music content processing, knowledge discovery, musicology (flamenco scholars), cognition, anthropology and literature.

–       Multi-cultural: How to refine music processing systems to be significant to people from different musical backgrounds and cultures.

So I am gathering nice ideas at this seminar!

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