#FEEL music through
emotion
Project overview

overview

Bridge Music Emotion Variation Detection and Affective Haptics through emotion.

Music Emotion Variation Detection

After collecting serial responses (valence and arousal) to music from 67 subjects and selecting five music features (frequency spectrum centroid, loudness, melodic pitch, tempo and number of instruments playing) for data analysis, Emery Schubert built OLS regression models that tell the serial correlations between music features and emotion responses.

Emotion

The affective factor embedded in musicology and haptics establishes the basis of our thinking that music can be a reflective source for tactile experience.

Affective Haptics

Many existing projects and works in the field of affective haptics have demonstrated and utilized the relationship between tactile experience and emotion. The innate experience known as synesthesia even shows the neurological evidence of the relationship.

Methodology

Hardware + Software + Implementation

Vibration jacket

Arduino

User interface

Processing

Experiment design

Qualitative + Quantitative methods

Milestone

The evolving research question, theoretical framework and demonstration.

  • 2016.3

    Tactile experience in live performance

    Our initial idea was that tactilization could synchronize with plots, music or choreography on the stage like what the fabric heart did in MatchAtria e x t e n d e d but in a way that users could manage and design their own tactile expression. The vibration jacket was built at this stage.

  • 2016.10

    Formation of project model

    Looked at relevant works and projects in the fields of Music Emotion Recognition, Music Emotion Variation Detection and Affective Haptics.

  • 2017.2

    Development of user interface

    Finish the design and implementation of user interface for the control of vibration motors.

  • 2017.3-4

    Experiment implementation

    Conduct the experiment of tactilization mapping and analyze data collected quantitatively and qualitatively. Conclusions and findings will be documented in thesis.


  • Iteration

Our team

Donghai Liu

Project leader

Aoxing Zhang

Data analyst

Michael Nitsche

Project advisor