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- W2017936404 abstract "The abstract nature of music makes it intrinsically hard to describe. To alleviate this problem we use well known songs or artists as a reference to describe new music. Music information research has mimicked this behavior by introducing search systems that rely on prototypical songs. Based on similarity models deducing from signal processing or collaborative filtering an according list of songs with similar properties is retrieved. Yet, music is often searched for a specific intention such as music for workout, to focus or for a comfortable dinner with friends. Modeling music similarities based on such criteria is in many cases problematic or visionary. Despite these open research challenges a more user focused question should be raised: Which interface is adequate for describing such intentions? Traditionally queries are either based on text input or seed songs. Both are in many cases inadequate or require extensive interaction or knowledge from the user.Despite the multi-sensory capabilities of humans, we primarily focus on vision. Many intentions for music searches can easily be pictorially envisioned. This paper suggests to pursue a query music by image approach. Yet, extensive research in all disciplinary fields of music research, such as music psychology, musicology and information technologies, is required to identify correlations between the acoustic and the visual domain. This paper elaborates on opportunities and obstacles and proposes ways to approach the stated problems." @default.
- W2017936404 created "2016-06-24" @default.
- W2017936404 creator A5006579329 @default.
- W2017936404 date "2014-09-12" @default.
- W2017936404 modified "2023-09-26" @default.
- W2017936404 title "A Picture is Worth a Thousand Songs" @default.
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- W2017936404 doi "https://doi.org/10.1145/2660168.2660185" @default.
- W2017936404 hasPublicationYear "2014" @default.
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