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. 

0168TrentGomezPoster

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