Emoticon: Toward the Simulation of Emotion Using Android Music Application
| Autor: | Anuj Kumar, Aditya Sahu, Akash Parekh |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
InformationSystems_INFORMATIONINTERFACESANDPRESENTATION(e.g.
HCI) business.industry Computer science Deep learning Recommender system Music player Facial recognition system Convolutional neural network Mood Human–computer interaction Emoticon Artificial intelligence Android (operating system) business |
| Zdroj: | Evolutionary Computing and Mobile Sustainable Networks ISBN: 9789811552571 |
| DOI: | 10.1007/978-981-15-5258-8_62 |
| Popis: | Music unquestionably affects our emotions. We tend to listen to music that reflects our mood. Music can affect our current emotional state drastically. Earlier, the user used to manually browse songs through the playlist. Over the period, recommendation systems have used collaborative and content-based filtering for creating playlist but not the current emotional state of the user. This paper proposes an idea of an android music player application which recommends songs after determining the user’s emotion by facial recognition at that particular moment using deep learning techniques. And create a playlist by considering the emotion of the user and recommending songs according to the current emotion of the user. |
| Databáze: | OpenAIRE |
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