Authors:
Miriam Allalouf
1
;
Avi Cohen
1
;
Lea Cohen Sabban
1
;
Ayelet Dassa
2
;
Sagi Marciano
1
and
Stella Melnitzer Beris
1
Affiliations:
1
Department of Software Engineering, Azrieli College of Engineering, Jerusalem, Israel
;
2
Department of Music, Bar-Ilan University, Ramat-Gan, Israel
Keyword(s):
Music Recommendation System, Music Metadata Mining, Music Information Retrieval, Digital Ageing, Dementia, Music-based Intervention, Machine Learning Algorithms, Music Repository.
Abstract:
The worldwide increase in life expectancy can be accompanied by age-related degenerative conditions such as dementia. Dementia poses significant challenges for which music is a beneficial non-pharmacological intervention. Based on research and clinical expertise we developed a web-based system, termed Tamaringa, that builds and displays customized playlists. The recommendation mechanism incorporates an old person's age, birthplace, and popular songs from their youth. That particular range is known as being most accessible to seniors in terms of memory. Although there are a lot of repositories containing metadata and information about music, there is no single repository that addresses all our requirements in terms of specific metadata, range query application programming interfaces (API) capability and popularity information. This study explores the APIs of several repositories in order to populate our internal database with suitable songs that are required for accurate personalized
recommendation. A preliminary promising pilot enabled twenty-four residents in an assisted living facility in Israel to engage and enjoy the music recommendation system. Personalized playlists were created using the system; the medical staff reports were positive. Further research will help to develop our system and eventually to integrate its use both in assisted living facilities and at home.
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