A Survey of Music Visualization Techniques

Music Information Research (MIR) comprises all the research topics involved in modeling and understanding music. Visualizations are frequently adopted to convey better understandings about music pieces, and the association of music with visual elements has been practiced historically and extensively. We investigated papers related to music visualization and organized the proposals into categories according to their most prominent aspects: their input features, the aspects visualized, the InfoVis technique(s) used, if interaction was provided, and users’ evaluations. The MIR and the InfoVis community can benefit by identifying trends and possible new research directions within the music visualization topic.

Designing, Implementing And Evaluating A Cross-Modal Sensory Substitution System For The Effective Communication Of The Emotional And Informative Aspects Of Music

Visualizations have existed for millennia as ways to communicate information. Visualizations are ubiquitous tools used every day to help navigate cities and aid in learning complex tasks. Tasks are made simpler when applying various visualization methods to large data sets to discover trends that are otherwise difficult to notice. More recently, music visualization systems have been created to convey music in the visual domain; however, they are not based on any psychological model of auditory and visual equivalents. This thesis discusses a music visualization system called MusicViz, which facilitates in the visual communication of the informative and entertainment aspect of music based on psychologically justified translation principals. MusicViz is combined with a vibro-feedback chair called the Emoti-Chair, which translates auditory music to vibrations along the user’s back. The combined system is coined VITA (Visually Immersive and Tactile Animation). A usability evaluation of the VITA showed it is an enjoyable experience.

Designing, Implementing And Evaluating A Cross-Modal Sensory Substitution System For The Effective Communication Of The Emotional And Informative Aspects Of Music

Visualizations have existed for millennia as ways to communicate information. Visualizations are ubiquitous tools used every day to help navigate cities and aid in learning complex tasks. Tasks are made simpler when applying various visualization methods to large data sets to discover trends that are otherwise difficult to notice. More recently, music visualization systems have been created to convey music in the visual domain; however, they are not based on any psychological model of auditory and visual equivalents. This thesis discusses a music visualization system called MusicViz, which facilitates in the visual communication of the informative and entertainment aspect of music based on psychologically justified translation principals. MusicViz is combined with a vibro-feedback chair called the Emoti-Chair, which translates auditory music to vibrations along the user’s back. The combined system is coined VITA (Visually Immersive and Tactile Animation). A usability evaluation of the VITA showed it is an enjoyable experience.

An Improved Particle Swarm Optimization-Powered Adaptive Classification and Migration Visualization for Music Style

Based on the adaptive particle swarm algorithm and error backpropagation neural network, this paper proposes methods for different styles of music classification and migration visualization. This method has the advantages of simple structure, mature algorithm, and accurate optimization. It can find better network weights and thresholds so that particles can jump out of the local optimal solutions previously searched and search in a larger space. The global search uses the gradient method to accelerate the optimization and control the real-time generation effect of the music style transfer, thereby improving the learning performance and convergence performance of the entire network, ultimately improving the recognition rate of the entire system, and visualizing the musical perception. This kind of real-time information visualization is an artistic expression form, in which artificial intelligence imitates human synesthesia, and it is also a kind of performance art. Combining traditional music visualization and image style transfer adds specific content expression to music visualization and time sequence expression to image style transfer. This visual effect can help users generate unique and personalized portraits with music; it can also be widely used by artists to express the relationship between music and vision. The simulation results show that the method has better classification performance and has certain practical significance and reference value.