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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
2016.
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:kth:diva-186867OAI: oai:DiVA.org:kth-186867DiVA: diva2:928312
Educational program
Master of Science in Engineering - Computer Science and Technology
Supervisors
Examiners
Available from: 2016-05-18 Created: 2016-05-15 Last updated: 2018-01-10Bibliographically approved

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fulltext(564 kB)155 downloads
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Strandberg, AronKarlström, Patrik
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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf