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.
Humans 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!
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:
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:
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.
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.
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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