Millions of tracks at the fingertips of music researchers

Aug 15, 2013
The attached figure shows certain tags and tracks in a two-dimensional emotion model. Credit: Pasi Saari / University of Jyväskylä

Online digital music services, such as Last.fm and Spotify, contain semantic information produced by users worldwide about millions of music tracks. A new method now enables exploiting this vast source of information in order to understand the processes behind expressions of musical moods.

Doctoral student Pasi Saari and Professor Tuomas Eerola, researchers at the Academy of Finland's Finnish Centre of Excellence in Interdisciplinary Music Research at University of Jyväskylä, investigated how reliable information social tags, user-generated free-form markings, convey about moods expressed by music. They also developed a new method based on semantic modeling to predict ratings of musical moods with online data. The study enables a giant leap forward in the size of research data – past research has exploited data in the size of few dozens to few hundreds of tracks.

The new method was developed using tags related to over one million tracks obtained from popular Last.fm service. About one fourth of the tracks contained mood tags, such as happy, chill-out, or powerful. A model resulting from several analysis stages could predict the semantic meaning of tags and tracks.

In a listening test 59 participants rated moods, such as energy/calmness, positive/negative, tension and sentimentality, in six hundred tracks from different genres. These ratings were then compared to the semantic estimates obtained with the new method.

Users of online social music services use tags often when searching or marking new interesting music, tracks from a certain genre, or to match the music to their own mood. Tags provide excellent material for music applications, since exploiting vast sources of information is a key to develop applications that can understand music more efficiently than before.

"When receiving an audio file, a could identify the moods expressed by music, genre and performer, or generate automatically a playlist for a certain person in a certain mood or for training music at gym," Pasi Saari describes.

Moods related to music are considered one of the main reasons why music is listened and performed in the first place. This is why understanding musical moods is important. Large-scale information helps to solve a problem of how to manage a collection that contains all tracks ever recorded.

Explore further: Modeling the ripples of health care information

More information: Saari, Pasi, and Tuomas Eerola. (in press, available online): Semantic Computing of Moods Based on Tags in Social Media of Music. IEEE Transactions on Knowledge and Data Engineering. DOI: 10.1109/TKDE.2013.128

add to favorites email to friend print save as pdf

Related Stories

In the mood for music

Jun 27, 2013

Could a computer distinguish between the moods of a mournful classical movement or an angst-ridden emo rock song? Research to be published in the International Journal of Computational Intelligence Studies, suggests that i ...

This is your brain on Vivaldi and Beatles

Aug 07, 2013

Listening to music activates large networks in the brain, but different kinds of music are processed differently. A team of researchers from Finland, Denmark and the UK has developed a new method for studying ...

Trying to be happier works when listening to upbeat music

May 14, 2013

The song, "Get Happy," famously performed by Judy Garland, has encouraged people to improve their mood for decades. Recent research at the University of Missouri discovered that an individual can indeed successfully try to ...

Streaming music gains in US market

Apr 02, 2013

Streaming music services like Pandora online radio are gaining fast among US listeners under age 35, a survey showed Tuesday.

Recommended for you

Forging a photo is easy, but how do you spot a fake?

Nov 21, 2014

Faking photographs is not a new phenomenon. The Cottingley Fairies seemed convincing to some in 1917, just as the images recently broadcast on Russian television, purporting to be satellite images showin ...

Algorithm, not live committee, performs author ranking

Nov 21, 2014

Thousands of authors' works enter the public domain each year, but only a small number of them end up being widely available. So how to choose the ones taking center-stage? And how well can a machine-learning ...

Professor proposes alternative to 'Turing Test'

Nov 19, 2014

(Phys.org) —A Georgia Tech professor is offering an alternative to the celebrated "Turing Test" to determine whether a machine or computer program exhibits human-level intelligence. The Turing Test - originally ...

User comments : 0

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.