Emotion Based Music Player System

ABSTRACT: –

Face Emotion Recognition is a process of image processing. Facial Emotion Recognition is the process of converting the movements of a person’s face into a digital database using various images processing technique.

 This database may then be used to produce CG, (computer graphics) computer animation for movies, games, or real-time avatars. Facial Emotion Recognition recognizes the face emotions. Recently, a number of new technologies for Facial Expression Recognition have been developed.

 This technique with equal contribution from AI filed can revolutionize the robotic industry. Human interaction with robots will reach completely new level as robots will be able to understand Human emotions & on the basis of those emotions a music player will be play.

SYSTEM:-

The system has the following modules:

• Face detection module: This module uses computer vision algorithms to detect the user’s face in real time and capture facial expressions. This model uses techniques such as the Haar cascade, the Viola-Jones algorithm, and deep learning-based face detection to detect faces.

• Emotion Detection Module: This module uses machine learning algorithms such as Support Vector Machine (SVM), Convolutional Neural Network (CNN), or Random Forest to identify user’s emotions based on facial expressions. This model analyzes the user’s facial expressions such as raising eyebrows, mouth and eye movements to determine emotional states.

• Music Selection Module: This module selects a music playlist based on mood.
• The module uses preset playlists based on emotions such as happiness, sadness, anger and surprise, or creates personalized playlists based on the user’s listening history and preferences. This model suggests using music using a recommendation engine based on the user’s mood and past listening patterns.

• Music Player Module: This module plays selected music playlists using a music player such as Spotify or YouTube. The module also includes functions such as skip, stop and volume control.

• User Feedback Module: This module accepts user feedback on the accuracy of music selection and emotional experience.
• This model uses feedback to improve music selection and cognitive algorithms.

Emotion Based Music Player System is the perfect app for music lovers who want to discover music according to their current mood. The system helps users discover new music and improve their thinking based on music selection playlists.

PROPOSED SYSTEM:-

This application uses face detection and mood recognition to determine the user’s mood and based on this, it gives a personalized play list. The face detection algorithm is based on OpenCV library and the mood detection part will be based on pattern matching. These implementations are designed in order to generate a playlist according to the user moods and offer these functionalities:

1. Set your mood & play songs.
2. Get your mood automatically by analyzing a periodical camera capture.

MODULES:-

Emotion Detection Module:

• Emotion Detection Module is an essential part of the music player. This model uses machine learning algorithms to detect the user’s emotional state based on the user’s face captured by face detection. This model has the following features:

• Feature Extraction: This model extracts facial features such as eye movement, eye movement, and mouth movement by capturing the face. This model uses techniques such as region detection and feature extraction to identify features using deep learning techniques such as convolutional neural networks (CNN).

• Emotion Classification: This model uses machine learning algorithms such as Support Vector Machine (SVM), Convolutional Neural Network (CNN) or Random Forest to classify user’s emotions based on extracted features.
• This model analyzes the extracted features and matches them with different emotions such as happiness, sadness, anger, and surprise. Integration with
• Music Selection Module: This module is used to select the appropriate music according to perceived needs, integrated with the Music Selection Module. This module transmits the emotional perception to the music selection module, which selects a suitable music playlist.

• Calibration: This model includes a calibration step to improve the accuracy of the cognitive algorithm. This module adjusts the classification algorithm based on user feedback to improve the accuracy of sensory recognition.

Emotional intelligence is an important part of the emotion-based music system. This model uses the most advanced computer and machine learning algorithms to analyze the user’s mood in real time, allowing the system to select the appropriate music according to the mood.

APPLICATION:-

Music system is an application that plays music in real time according to the user’s facial expression. The application uses computer video algorithms to determine emotions such as happiness, sadness, anger, surprise on the user’s face and selects the appropriate music according to the views.

The application has the following features:

• Face Detection: The application uses computer vision algorithms to identify the user’s face and capture the face in real time.

• Emotion Detection: This app uses machine learning algorithms to detect user’s emotions based on facial expressions. The app analyzes the user’s facial expressions such as raised eyebrows, mouth and eye movements to identify emotional states.
• Music selection: The app selects the music playlist according to the mood. The app uses preset playlists based on emotions such as happiness, sadness, anger, and surprise, or creates personalized playlists based on the user’s listening history and preferences.

• Music Player: The application uses music sources such as Spotify or YouTube to play the selected music. The app also includes features like skip, pause and volume control.

• User Feedback: The app collects user feedback on music choices and real emotional experiences.
• The app uses feedback to improve music selection and cognitive algorithms.

Emotion-Based Music Player System is an easy-to-use application that offers a unique musical experience according to the user’s mood. The app helps users find new music and improve their mood based on music selection.

HARDWARE AND SOFTWARE REQUIREMENTS:-

HARDWARE:-

·        Processor: Pentium 4

·        RAM: 512 MB or more

·        Hard disk: 16 GB or more

·        Web Camera.

SOFTWARE:-

• Java JDK 7
• NetBeans 7.2
• Windows Operating System.