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- The resulting decision tree and analysis of this interpretable model makes it possible to find predictive factors that influence therapeutic music listening outcomes. The strong subjectivity of therapeutic music listening suggests the use of machine learning techniques as an important and innovative approach to supporting music therapy practice.
www.sciencedirect.com/science/article/pii/S0169260719301555Machine learning techniques to predict the effectiveness of ...
Jan 14, 2023 · The experiment aims to create a machine-learning model that can predict whether a specific song has therapeutic effects on a specific person. The model considers a person’s musical and emotional characteristics but is also trained to consider solfeggio frequencies.
- 10.3390/s23020986
- 2023/01
- Sensors (Basel). 2023 Jan; 23(2): 986.
Jun 30, 2023 · An AI model trained on these immersion signals predicted hit songs with high accuracy, the researchers reported. In contrast, participants' ranking of how much they enjoyed a song did...
Mar 1, 2020 · The resulting decision tree and analysis of this interpretable model makes it possible to find predictive factors that influence therapeutic music listening outcomes. The strong subjectivity of therapeutic music listening suggests the use of machine learning techniques as an important and innovative approach to supporting music therapy practice.
- Alfredo Raglio, Marcello Imbriani, Chiara Imbriani, Paola Baiardi, Sara Manzoni, Marta Gianotti, Mau...
- 2020
Jun 20, 2023 · A logistic regression model trained on neurophysiologic responses for the 1st min of songs correctly classified hits with 77% accuracy and flops with 56% accuracy ( N = 10,000). The bagged machine learning model classified 74% of songs correctly.
- Sean H. Merritt, Kevin Gaffuri, Paul J. Zak
- Front Artif Intell. 2023; 6: 1154663.
- 10.3389/frai.2023.1154663
- 2023
Oct 29, 2019 · The experiment aims to create a machine-learning model that can predict whether a specific song has therapeutic effects on a specific person and considers a person’s musical and emotional characteristics but is also trained to consider solfeggio frequencies.
Here, we present a study to establish the main predictive factors of music listening's relaxation effects using machine learning methods. Methods: Three hundred and twenty healthy participants were evenly distributed by age, education level, presence of musical training, and sex.
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Does machine learning influence therapeutic music listening outcomes?
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Can machine learning support music therapy practice?
How accurate is machine learning in identifying hit songs?
Can machine learning make a song a hit?
Does a bagged machine learning model predict hits?
Oct 1, 2019 · The current paper focuses on identifying and predicting whether music has therapeutic benefits. A machine learning model is developed, using a multi-class neural network to classify...
