Reconstructing music directly from brain activity provides insight into the neural representations underlying auditory processing and paves the way for future brain-computer interfaces. We introduce a fully data-driven pipeline that combines cross-su...
Generative deep learning models, such as those used for music generation, can produce a wide variety of results based on perturbations of random points in their latent space. User preferences can be incorporated in the generative process by replacing...
String instrument timbre is influenced by a complex interplay of string material, instrument body characteristics, and playing technique. However, the perceptual effects of different string materials and their relationship with acoustic parameters re...
With the rapid development of music streaming platforms, accurate understanding of lyric emotions has become crucial for enhancing personalized services in music recommendation systems. However, existing methods show significant limitations in proces...
The ability to generate dynamic, expressive dance routines that adapt to various musical compositions has broad applications in activity recognition, performance arts, entertainment, virtual reality, and interactive media, offering new avenues for cr...
In the context of the digital transformation of ideological and political education (IPE) in the new era, this study explores the interdisciplinary integration of red music and intelligent recommendation technologies. An intelligent deep learning mod...
Music Genre is an abstract property of music that can identify shared traditions and conventions. In the recent past, music genre classification has shown a significant role in MIR that has attracted the research community to draw attention all aroun...
Creative experiences may enhance brain health, yet metrics and mechanisms remain elusive. We characterized brain health using brain clocks, which capture deviations from chronological age (i.e., accelerated or delayed brain aging). We combined M/EEG ...
Natural environments typically contain a blend of simultaneous sounds. A substantial challenge in neuroscience is identifying specific neural signals corresponding to each sound and analyzing them separately. Combining frequency tagging and machine l...
Dance is often perceived as complex due to the need for coordinating multiple body movements and precisely aligning them with musical rhythm and content. Research in automatic dance performance assessment has the potential to enhance individuals' sen...
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