Text 1
Attempts to automate classification of music into genres have not been very successful. It is also unclear whether categorizing music by genre is useful, since genre categories are ambiguous, subjective, and reductive. As Jin Ha Lee and Anh Thu Nguyen argue in their study of the South Korean band BTS, relationships between pieces of music may be best understood with concepts other than genre.
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Merengue is a genre of music originally from the Dominican Republic that shares some harmonic and rhythmic similarities with the axé genre. Automated genre classification systems typically struggle to draw distinctions in situations like this, but Yandre Costa and colleagues solved that problem by converting sound to images and having computers compare features of those images. Their approach could improve genre classification, which could have many benefits for users.
Attempts to automate classification of music into genres have not been very successful. It is also unclear whether categorizing music by genre is useful, since genre categories are ambiguous, subjective, and reductive. As Jin Ha Lee and Anh Thu Nguyen argue in their study of the South Korean band BTS, relationships between pieces of music may be best understood with concepts other than genre.
Text 2
Merengue is a genre of music originally from the Dominican Republic that shares some harmonic and rhythmic similarities with the axé genre. Automated genre classification systems typically struggle to draw distinctions in situations like this, but Yandre Costa and colleagues solved that problem by converting sound to images and having computers compare features of those images. Their approach could improve genre classification, which could have many benefits for users.