All Outputs (3)

Genre-adaptive Semantic Computing and Audio-based Modelling for Music Mood Annotation (2015)
Journal Article
Saari, P., Fazekas, G., Eerola, T., Barthet, M., Lartillot, O., & Sandler, M. (2016). Genre-adaptive Semantic Computing and Audio-based Modelling for Music Mood Annotation. IEEE Transactions on Affective Computing, 7(2), 122-135. https://doi.org/10.1109/taffc.2015.2462841

This study investigates whether taking genre into account is beneficial for automatic music mood annotation in terms of core affects valence, arousal, and tension, as well as several other mood scales. Novel techniques employing genre-adaptive semant... Read More about Genre-adaptive Semantic Computing and Audio-based Modelling for Music Mood Annotation.

Semantic Computing of Moods Based on Tags in Social Media of Music (2014)
Journal Article
Saari, P., & Eerola, T. (2014). Semantic Computing of Moods Based on Tags in Social Media of Music. IEEE Transactions on Knowledge and Data Engineering, 26(10), 2548-2560. https://doi.org/10.1109/tkde.2013.128

Social tags inherent in online music services such as Last.fm provide a rich source of information on musical moods. The abundance of social tags makes this data highly beneficial for developing techniques to manage and retrieve mood information, and... Read More about Semantic Computing of Moods Based on Tags in Social Media of Music.

Generalizability and Simplicity as Criteria in Feature Selection: Application to Mood Classification in Music (2011)
Journal Article
Saari, P., Eerola, T., & Lartillot, O. (2011). Generalizability and Simplicity as Criteria in Feature Selection: Application to Mood Classification in Music. IEEE Transactions on Audio, Speech and Language Processing, 19(6), 1802-1812. https://doi.org/10.1109/tasl.2010.2101596