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A game interface for annotating emotion in music
Název práce v češtině: Herní rozhraní pro anotaci emocí v hudbě
Název v anglickém jazyce: A game interface for annotating emotion in music
Klíčová slova: emoce v hudbě|gamifikace|anotační rozhraní
Klíčová slova anglicky: emotion in music|gamification|annotation interface
Akademický rok vypsání: 2022/2023
Typ práce: bakalářská práce
Jazyk práce: angličtina
Ústav: Ústav formální a aplikované lingvistiky (32-UFAL)
Vedoucí / školitel: Mgr. Jan Hajič, Ph.D.
Řešitel: Reut Tal - zadáno a potvrzeno stud. odd.
Datum přihlášení: 20.09.2023
Datum zadání: 20.09.2023
Datum potvrzení stud. oddělením: 23.11.2023
Zásady pro vypracování
Systematizing and predicting the emotional content of music is one of the key tasks in the personalized music distribution paradigm of today, also in the context of music generation systems. As this is done at scale primarily using machine learning methods, predicting emotional content and impact of music requires extensive training data with human annotations. Collecting this data is usually done through questionnaires, but this explicit design imposes an artificial context in which the responses are gathered.

This thesis aims to embed the collection of human emotional labels for music in a game. A play-through should take no more than 20-30 minutes, which is a typical time a questionnaire takes. The researcher is responsible for populating the game with a selection of music (whether real or generated) that is the subject of data collection. Then, in order to communicate with non-player characters and advance the game’s narrative, players will select musical fragments according to solicited emotions from a predefined standard emotional model – thus providing emotion labels for the musical fragments as part of gameplay. This way, we aim to collect emotion labels in a less ostentatious manner than questionnaires, as part of a principally engaging experience.
Seznam odborné literatury
Eerola, Tuomas, and Jonna K. Vuoskoski. "A comparison of the discrete and dimensional models of emotion in music." Psychology of Music 39.1 (2011): 18-49.
https://journals.sagepub.com/doi/pdf/10.1177/0305735610362821?casa_token=5asoVdI4ts4AAAAA:IkbDRK5wbXv9eVUoPrXJ3nJ6dWu9o67620w6m8kmI2U6557L0n5lKN_DUT5tFjwRh_1xPCPZC4M

Juslin, Patrik N., and Petri Laukka. "Expression, perception, and induction of musical emotions: A review and a questionnaire study of everyday listening." Journal of new music research 33.3 (2004): 217-238.
https://www.tandfonline.com/doi/pdf/10.1080/0929821042000317813

Laurier, Cyril, et al. "Exploring relationships between audio features and emotion in music." ESCOM 2009: 7th Triennial Conference of European Society for the Cognitive Sciences of Music. 2009.
https://jyx.jyu.fi/bitstream/handle/123456789/20889/1/urn_nbn_fi_jyu-2009411271.pdf

Shingjergji, Krist, et al. "Interpretable explainability in facial emotion recognition and gamification for data collection." 2022 10th International Conference on Affective Computing and Intelligent Interaction (ACII). IEEE, 2022.
https://arxiv.org/pdf/2211.04769.pdf
 
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