Multimodal Music Mood Classification Framework for Kokborok Music

Das, S. R.; Satpathy, Sambit; Debbarma, Swapan

doi:10.1007/978-981-33-4299-6_14

Cited by 7 publications

(5 citation statements)

References 9 publications

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“…The resources inside the school represent the prescribed resources provided by the school, while the resources outside the school represent the resources that students can choose independently. Third, in the “professional-general” dimension, it includes professional resources and general resources in music education ( Das and Satpathy, 2021 ).…”

Section: The Path and Methods Of Music Psychology In Music Teachingmentioning

confidence: 99%

RETRACTED: The approaches and methods of music psychology in the relationship between music emotion and cognition in music teaching activities

Nan

Yang

2022

Front. Psychol.

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In order to further improve the effect of music teaching, more music psychology should be applied in music teaching to assist teaching, and students should better understand the emotional elements reflected in music through music emotion and cognitive teaching. This essay starts from the relationship between music emotion and cognition, to deeply explore the application of music psychology in teaching activities, through the construction of music education psychological regulation function model to explore the effect of the application of psychology in music teaching. The results showed that the scores of positive emotions were significantly improved, while the scores of negative emotions were significantly decreased. The difference between the improvement and reduction of positive emotions was significant (p < 0.01, p < 0.01). The results show that psychology based on the relationship between emotions and people is helpful to improve the effectiveness of music teaching. And on this basis put forward the music teaching activity innovation path.

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Section: The Path and Methods Of Music Psychology In Music Teachingmentioning

confidence: 99%

RETRACTED: The approaches and methods of music psychology in the relationship between music emotion and cognition in music teaching activities

Nan

Yang

2022

Front. Psychol.

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“…Yang suggested that collaborative filtering should be combined with user context information, and the original user-data scoring model of collaborative filtering should be expanded to form a three-dimensional data model of user-data-context, and the correlation dimension should be expanded to achieve more accurate personalised recommendation [ 11 ]. Das suggested using 12-order mel-frequency cepstral coefficients MFCC (MFCC) and 1-order energy to represent music perception characteristics and using nearest neighbor algorithm as classifier [ 12 ]. Chen suggested to compare four multilabel classification algorithms.…”

Section: Related Workmentioning

confidence: 99%

[Retracted] Music Classification Method Using Big Data Feature Extraction and Neural Networks

2022

Journal of Environmental and Public Health

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From the cassette era to the CD era to the digital music era, the quantity of music has grown rapidly. People cannot easily search for the desired music without classifying enormous music resources and developing a successful music retrieval system. By examining users’ historical listening patterns for personalised recommendations, the music recommendation algorithm can lessen message fatigue for users and enhance user experience. Relying on manual labelling is how traditional music is classified. It would be inefficient and unrealistic to attempt to classify music using manual labelling in the age of big data. Feature extraction and neural networks are the tools employed in this paper. The model’s parameters can be trained using conventional gradient descent techniques, and the model’s trained convolution neural network can learn the image’s features and finish the extraction and classification of the features. This algorithm is 12 percent superior to the conventional algorithm, according to the research in this paper. It has strong ability and is appropriate for widespread implementation with the same number of iterations.

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“…Das and Satpathy used CNN to extract multiple features from music signals and classify them [ 11 ]. Experiments on the GTZAN dataset show that this method can effectively improve music style recognition using a single feature.…”

Section: Related Workmentioning

confidence: 99%

[Retracted] Automatic Music Classification Model Based on Instantaneous Frequency and CNNs in High Noise Environment

Jia

2022

Journal of Environmental and Public Health

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Automatic music classification has significant research implications because it is the foundation for quick and efficient music resource retrieval and has a wide range of possible applications. In this study, DL is used to extract and categorize musical features, and a DL-based model for music feature extraction and classification is created. In this study, the instantaneous frequency and short-time Fourier transform are used to estimate the sine of a mixed music signal. Based on peak-frequency pairs, the DL algorithm is then used to calculate multiple candidate pitch estimates for each frame, and the melody pitch sequence is then obtained in accordance with the pitch profile duration and continuity characteristics. With this approach, the pitch can be calculated without reference to the fundamental frequency component. A music feature classification approach using spectrogram as input data and CNN as classifier is proposed at the same time in light of CNN’s benefits in image processing. Studies reveal that this model’s categorization and music feature extraction accuracy is as high as 94.18 percent and 95.66 percent, respectively. The outcomes demonstrate the efficiency of this technique for the extraction and classification of musical features. The field of music information retrieval is a good fit for it.

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Multimodal Music Mood Classification Framework for Kokborok Music

Cited by 7 publications

References 9 publications

RETRACTED: The approaches and methods of music psychology in the relationship between music emotion and cognition in music teaching activities

RETRACTED: The approaches and methods of music psychology in the relationship between music emotion and cognition in music teaching activities

[Retracted] Music Classification Method Using Big Data Feature Extraction and Neural Networks

[Retracted] Automatic Music Classification Model Based on Instantaneous Frequency and CNNs in High Noise Environment

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