Implementation of the Audio Feature Extraction Module System from the Detection in the Human Emotions
Abstract
The mood of an
individual person is usually recognized based on their facial expressions. With
today’s technologies, distinguishable features of the face can be extracted as
inputs with the help of a webcam or any other external device. The gathered
data helps in detecting the mood and songs are played from a personalized
playlist, if available or a default playlist can be used based on the mood
detected. This removes the time-consuming and tedious task of manually grouping
songs into different lists and helps in generating an appropriate playlist
based on an individual’s emotional features. Thus, our proposed system mainly
aims on detecting human emotions for developing emotion-based music player. A
brief idea about our systems working, playlist generation and emotion
classification is mentioned below.
Country : India
1 G Naga Kumar Kakarla
Associate Professor, Department of Computer Science and Engineering, Malla Reddy College of Engineering for Women, Hyderabad -500100, Telangana, India
IRJIET, Volume 1, Issue 3, December 2017 pp. 40-44
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EMOTION BASED MUSIC RECOMMENDATION
SYSTEM H. Immanuel James, J. James Anto Arnold, J. Maria Masilla Ruban, M.
Tamilarasan, R. Saranya IRJET (2019)
Ali Mollahosseini, Behzad Hasani and
Mohammad H. Mahoor 2017, “AffectNet: A Database for Facial Expression, Valence,
and Arousal Computing in the Wild”, arXiv:1708.03985v4[cs.CV],10/2017
Emophony – Face Emotion Based Music
Player Banpreet Singh Chhabra – IRJET (JUNE 2020)
Seungjae Lee, Jung Hyun Kim, Sung Min
Kim, & Won Young Yoo. (2011). Smoodi: Mood-based music recommendation
player, 2011 IEEE International Conference on Multimedia and Expo.
