Exposition

Aimpathy (2023)

Amit Yungman
open exposition

About this exposition

Much research has been done to better understand the emotional experience of music; from the philosophical, artistic, psychological, and statistical approaches. In this research we conduct a cross-domain experiment based on those four disciplines, to further understand the factors that influence the emotional perception of music; and in particular the difference between the artist’s emotional conception and the audience’s perception. In the experiment we train a novel model of an Artificial Neural Network, to predict the perceived emotion from a short musical phrase. We then feed the machine curated input, which simulates artistic choices, to explore its most significant factors in determining the perceived emotions. In the conclusion we describe the results, as well as the possible follow-ups to the experiment, such as an emotional expression training tool for musicians.
typeresearch exposition
keywordsemotion, music, perception, expression, neural network, emotions, Artificial Intelligence (AI), Data Science
date09/11/2022
published15/05/2023
last modified15/05/2023
statuspublished
share statusshared with registered RC users
copyrightAmit Yungman
licenseCC BY-NC-ND
languageEnglish
urlhttps://www.researchcatalogue.net/view/1790959/1790960
published inKC Research Portal
portal issue1. Master Research Projects


Simple Media

id name copyright license
1933164 Simple ANN Amit Yungman Public domain
1933173 Multi-layer ANN Amit Yungman Public domain
1933183 Paragraph Amit Yungman Public domain
1933204 A CNN Amit Yungman Public domain
1933211 Paragraph Amit Yungman Public domain
1933220 Audioform Amit Yungman Public domain
1933222 Spectrogram Amit Yungman Public domain
1933230 Thayers-Model-for-the-Emotional-Plane-also-named-Russels-model Photo from Nguyen, Van Loi & Kim, Donglim & Ho, V.P. & Lim, Younghwan. (2017). A New Recognition Method for Visualizing Music Emotion. International Journal of Electrical and Computer Engineering. 7. 1246-1254. 10.11591/ijece.v7i3.pp1246-1254. Public domain
1934752 Dataset architecture - simple Amit Yungman Public domain
1934774 Dataset architecture - simple Amit Yungman Public domain
1934801 Dataset architecture - simple Amit Yungman Public domain
1936605 Dataset architecture - detailed Amit Yungman Public domain
1945695 Single tone comparison - Valence Amit Yungman Public domain
1945702 Result - single tone no memory Amit Yungman Public domain
1945712 Subparagraph Amit Yungman Public domain
1945736 Single tone results - with memory Amit Yungman Public domain
1945818 Chromatic scale results - with memory Amit Yungman Public domain
1945890 Continuous note vs. harmony - with memory Amit Yungman Public domain
1946197 Tempo change results - With memory Amit Yungman Public domain
1946204 Tempo change results - No memory Amit Yungman Public domain
1946209 Volume change results - With memory Amit Yungman Public domain
1946236 Single tone no beat Amit Yungman Public domain
1946237 Single tone - beat and no beat Amit Yungman Public domain
1946238 Chromatic scale Amit Yungman Public domain
1946239 Harmony Amit Yungman Public domain
1946240 Tempo change Amit Yungman Public domain
1946241 Volume faded change Amit Yungman Public domain
1946243 Volume fade and sharp change Amit Yungman Public domain
1946247 LSTMCNN - Jupyter Notebook - Google Chrome_9 Amit Yungman Public domain
1946248 Single tone no beat Amit Yungman Public domain
1946259 Single tone - memory True Amit Yungman Public domain
1946260 Single tone no beat - memory True Amit Yungman Public domain
1946263 Tempo change - memory True Amit Yungman Public domain
1946264 Volume faded change - memory True Amit Yungman Public domain
1946265 Volume sharp change - memory True Amit Yungman Public domain
1946287 Single tone no beat - memory False Amit Yungman Public domain
1946291 Single tone - memory False Amit Yungman Public domain
1946295 Tempo change - memory False Amit Yungman Public domain
1946299 Volume faded change - memory False Amit Yungman Public domain
1946303 Volume sharp change - memory False Amit Yungman Public domain
1946361 Aimpathy tool demonstration - Made with Clipchamp Amit Yungman Public domain
1948999 one_tone_A Amit Yungman Public domain
1949028 one_tone_C Amit Yungman Public domain
1949039 chromatic_8_scale_down Amit Yungman Public domain
1949042 chromatic_8_scale_up Amit Yungman Public domain
1949051 one_tone_A_120_bpm Amit Yungman Public domain
1949053 one_tone_C_120_bpm Amit Yungman Public domain
1949091 Harmony_A_C_one_tone Amit Yungman Public domain
1949093 Harmony_A_C_120_bpm Amit Yungman Public domain
1949095 Harmony_A_Cs_one_tone Amit Yungman Public domain
1949097 Harmony_A_Cs_120_bpm Amit Yungman Public domain
1949099 volume_decrease_fade Amit Yungman Public domain
1949101 volume_increase_fade Amit Yungman Public domain
1949102 volume_decrease_sharp Amit Yungman Public domain
1949104 volume_increase_sharp Amit Yungman Public domain
1949105 A_decreasing_bpm Amit Yungman Public domain
1949107 A_increasing_bpm Amit Yungman Public domain

comments: 1 (last entry by Johannes Boer - 18/02/2023 at 14:11)