Tag Archives: semantic audio

Correlation between musical descriptors and emotions recognized in Beethoven’s Eroica

Last Wednesday I presented a poster at the Ninth Triennial Conference of the European Society for the Cognitive Sciences of Music (ESCOM 2015), that took place at the Royal Northern College of Music, Manchester, UK. It was a very interesting conference, including a very nice symposium in understanding musical audiences and inspiring talks on music education, psychology and wellbeing. Really impressed by how music have influence to improve quality of live from early years to the end of our lives.

The work I presented was leaded by Erika Trent, a student from the MIT that spent last summer at my lab thanks to the MIT Spain program. It was a very productive stay!

In this study we analysed the emotions that listener perceive when listening to Beethoven Symphony No. 3, Eroica, PHENICX target piece, played by the Royal Concertgebouw Orchestra Amsterdam. We then quantify the correlation between listeners’ perceived emotions from music and 1) musical descriptors, and 2) listeners’ backgrounds (country of origin, musical knowledge, exposure to classical music and knowledge of Eroica).

One conclusion of this study is that tonal strength (i.e. key clarity) correlates significantly with listener ratings of peacefulness, joyful activation, tension and sadness. Other significant correlations between emotion ratings and musical descriptors agree with the literature. This agreed with our hypothesis, being different parts on the same musical piece.

But there are two other unexpected and interesting findings that we might need to continue researching on.

First, we found out that listeners of varying backgrounds agree most on their ratings of sadness, compared to other emotions. Would that be similar for other musical pieces?

Second, listeners of similarly unmusical backgrounds, and listeners of young ages, recognise similar emotions to same music. On the contrary, listeners with more musical experience recognise different emotions to the same music. Caused by personal biases?

Interesting results that might corroborate the need for personalisation in music recommendation engines!

You can read the whole paper and access the poster here. 


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Academic visit to Queen Mary University of London

I am spending the summer (June-September 2015) at the Centre for digital Music, Queen Mary University of London, thanks to a José de Castillejo Fellowship from the Spanish Government.

During my stay, I am collaborating with Simon Dixon, trying to understand the criteria people use to transcribe flamenco singing, and analyse the influence of musical knowledge and exposure to flamenco music. Our ultimate goal is to improve current methods for automatic transcription, specially for this particular music.

At the same time I am getting familiar to all wonderful work carried out at C4DM, specially in the FAST_IMPACt project, leaded by Prof. Mark. Sandler. It is an EPSRC-funded research project combining Audio & Music Technology, Semantic Web, e-Science and Human-Computer Interaction, where I am part of the advisory board.

I already attended a couple of interesting events! London is a wonderful city, specially for researchers in music technology.

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