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Processing Natural Language for the Spotify API: Are sophisticated natural language processing algorithms necessary when processing language in a limited scope?
KTH, School of Computer Science and Communication (CSC).
KTH, School of Computer Science and Communication (CSC).
2016 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAlternative title
Bearbetning av Naturligt Spr ̊ak till Spotifys API (Swedish)
Abstract [en]

Knowing whether you can implement something complex in a simple way in your application is always of interest. A natural language interface is some- thing that could theoretically be implemented in a lot of applications but the complexity of most natural language processing algorithms is a limiting factor.

The problem explored in this paper is whether a simpler algorithm that doesn’t make use of convoluted statistical models and machine learning can be good enough. We implemented two algorithms, one utilizing Spotify’s own search and one with a more accurate, o✏ine search.

With the best precision we could muster being 81% at an average of 2,28 seconds per query this is not a viable solution for a complete and satisfactory user experience. Further work could push the performance into an acceptable range. 

Place, publisher, year, edition, pages
National Category
Computer Science
URN: urn:nbn:se:kth:diva-186867OAI: diva2:928312
Educational program
Master of Science in Engineering - Computer Science and Technology
Available from: 2016-05-18 Created: 2016-05-15 Last updated: 2016-05-18Bibliographically approved

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Strandberg, AronKarlström, Patrik
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