Intelligent multimodal analysis of musical time-series: an approach to mental health estimatio

Key Points

• This study aims to explore how multimodal analysis of musical time-series can estimate mental health conditions.
• Utilized machine learning algorithms for data analysis.
• Analyzed various musical time-series data to identify correlations with mental health.
• Employing a diverse dataset to enhance the robustness of findings.
• Found significant correlations between musical features and mental health indicators.
• Achieved improved estimation accuracy through intelligent data fusion techniques.

Abstract