Recognition of musical emotions in the behavioral variant of frontotemporal dementia

Orjuela-Rojas, Juan Manuel; Montañés, Patricia; Rodríguez, Ingrid Lizeth Lizarazo; Marín, Néstor Ricardo González

doi:10.1016/j.rcp.2020.01.002

Cited by 2 publications

(1 citation statement)

References 34 publications

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“…With the continuous development of science and technology and electronic products, piano music recognition technology has also been further developed. e piano performance recognition technology has been transformed from the indoor research process to the market application stage and has developed to a relatively high level [1][2][3]. At present, the focus of domestic and foreign research is on the continuous performance of a nonspecific player.…”

Section: Introductionmentioning

confidence: 99%

Multimedia Recognition of Piano Music Based on the Hidden Markov Model

Zhu

2021

Advances in Multimedia

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Piano performance is an art with rich artistic elements and unpredictable performance skills. It is an important carrier for playing beautiful piano sounds. The generation of musical tension and expression of piano performance is a vivid display of piano performance skills. In piano performance, we should pay attention to the cultivation and flexible application of performance skills. In order to ensure the richness and artistry of piano performance, it is fully based on the artistic characteristics of piano performance. Through in-depth analysis of the principle of the hidden Markov model, it is applied to the multimedia recognition process of piano playing music. In the process of obtaining the template, the fundamental frequency of the piano playing music differs greatly, and the piano playing music appears during the performance process. For the problem of low recognition rate, this paper proposes a multimedia recognition method for piano music. Finally, the analysis of experimental results shows that the method proposed in this paper has a 16% higher recognition rate than the traditional method, and it has a certain value in the multimedia recognition of piano music.

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Section: Introductionmentioning

confidence: 99%

Multimedia Recognition of Piano Music Based on the Hidden Markov Model

Zhu

2021

Advances in Multimedia

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RETRACTED: Fuzzy control algorithm for analyzing the effects of vocal music on college students’ social and emotional learning

Yang

2024

IFS

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Vocal music training for college students impacts the social and emotional aspects of better learning. This impact must be classified progressively to improve the social and musical connectivity coinciding with real-time emotions. Therefore, an intermittent analysis of music learning is required for augmenting socio-emotional changes to the learning method. This article introduces Impact-centric Learning Analysis (ILA) using the Fuzzy Control Algorithm (FCA) for the purpose above. The control algorithm operates in two linear stages: in the first stage, the socio-emotional impact of the learning on the students is analyzed, pursued by the learning changes in the second stage. This first stage inputs student activity scores based on real-time implications. The lowest scores are classified independently in the second stage, and learning changes are carried out. The learning change is targeted to meet the maximum (optimal) impact score from the first stage using fuzzy differentiations based on training sessions and student performance. Therefore, the proposed algorithm generates an optimal impact for the considered features (socio-emotional), preventing trivial vocal music sessions.

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Recognition of musical emotions in the behavioral variant of frontotemporal dementia

Cited by 2 publications

References 34 publications

Multimedia Recognition of Piano Music Based on the Hidden Markov Model

Multimedia Recognition of Piano Music Based on the Hidden Markov Model

RETRACTED: Fuzzy control algorithm for analyzing the effects of vocal music on college students’ social and emotional learning

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