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Beschreibung
One of the most attractive functions of music is that it can convey emotion and modulate a listener's mood. Music can bring to tears, console us when we are grieving and drive us to love. Music information behaviour studies have identified emotion as an important criterion used by people in music searching and organization. Hence, it becomes more and more significant the role of music emotion recognition. The automatization of the perceived emotion recognition in music allows users to organize and to research in a content-centric fashion. Purpose of this study is to find a link between music and emotions during the listening of a song by combining audio and physiological signals analysis. Inclusion of emotions is found to be an hard task, due to the subjective nature of emotion perception. There are problems in the reliability of ground truth data and evaluation of prediction results, all issues that are not present in other data-driven tasks, like for example face recognition or speech recognition.
One of the most attractive functions of music is that it can convey emotion and modulate a listener's mood. Music can bring to tears, console us when we are grieving and drive us to love. Music information behaviour studies have identified emotion as an important criterion used by people in music searching and organization. Hence, it becomes more and more significant the role of music emotion recognition. The automatization of the perceived emotion recognition in music allows users to organize and to research in a content-centric fashion. Purpose of this study is to find a link between music and emotions during the listening of a song by combining audio and physiological signals analysis. Inclusion of emotions is found to be an hard task, due to the subjective nature of emotion perception. There are problems in the reliability of ground truth data and evaluation of prediction results, all issues that are not present in other data-driven tasks, like for example face recognition or speech recognition.
Über den Autor
Gioele graduated with honours at Politecnico di Milano in Computer Science, Sound and Music engineering. He's a flute player, constantly looking for new paradigms to combine music and engineering.
Details
Erscheinungsjahr: 2020
Genre: Importe, Musik
Rubrik: Kunst & Musik
Thema: Musiktheorie & Musiklehre
Medium: Taschenbuch
Inhalt: 128 S.
ISBN-13: 9786200837721
ISBN-10: 6200837724
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Pozzi, Gioele
Hersteller: Edizioni Accademiche Italiane
Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, D-49078 Osnabrück, mail@preigu.de
Maße: 220 x 150 x 9 mm
Von/Mit: Gioele Pozzi
Erscheinungsdatum: 18.06.2020
Gewicht: 0,209 kg
Artikel-ID: 118540798

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