Emotion Based Music Player - XBeats

International Journal of Advance Research Ideas and Innovations in Technology

One of the most essential components of an individual's body is the human face and it acts as the main indicator for the behavioural and the emotional state of the individual face and it's very important for the human to extracting the required input from the human face can be done by using the camera directly. The mean of this examination is making Facial Expression Recognition (FER) conspire by Utilizing the CNN Algorithm and tensor flow to recognize the face by the camera. Facial expression analysis is used in a different way to detect human emotions. There are four types of emotions are recognized: happy, sad, angry, neutral depends on the mood. The playlist itself have the songs in the database, it plays the songs according to the mood detect by the Camera. This research paper is effective because we are using the different algorithm i.e. CNN model which is based on Machine Learning which gives accuracy and reduces the time to recognize the emotions.

IRJET, 2022

A user's emotion or mood can be detected by his/her facial expressions. These expressions can be derived from the live feed via the system's camera. A lot of research is being conducted in the field of Computer Vision and Machine Learning, where machines are trained to identify various human emotions or moods. Machine Learning provides various techniques through which human emotions can be detected. Music is a great connector. Music players and other streaming apps have a high demand as these apps can be used anytime, anywhere and can be combined with daily activities, traveling, sports, etc. People often use music as a means of mood regulation, specifically to change a bad mood, increase energy level or reduce tension. Also, listening to the right kind of music at the right time may improve mental health. Thus, human emotions have a strong relationship with music. In our proposed system, a mood-based music player is created which performs real time mood detection and suggests songs as per detected mood. The objective of this system is to analyze the user's image, predict the expression of the user and suggest songs suitable to detect mood.

International Journal for Research in Applied Science & Engineering Technology (IJRASET), 2023

This research constructs a face emotion framework that can examine fundamental human facial expression. The approach suggested was used by humans to classify the humans' mood and eventually to play the audio file that links to human emotion using this result. First of all, the device takes the face of the human being as a part of the process. It is carried out facial recognition. After this, the human face can be recognized using attribute extraction techniques. This way the emotion of humans can be identified using the image element. Those signature points are located by the extraction of tongue, mouth and eyebrows, eyebrow. If the input face precisely matches the emotion dataset face, we will detect individual feelings to play the emotional audio file. Training with a small range of characteristics faces can gain recognition in varying environmental conditions. An easy, effective and reliable solution is proposed. In the field of identification and detection, system plays a very important part.

Human expression plays a vital role in determining the current state and mood of an individual, it helps in extracting and understanding the emotion that an individual has based on various features of the face such as eyes, cheeks, forehead or even through the curve of the smile. Music is basically an art form that soothes and calms human brain and body. Taking these two aspects and blending them together our project deals with detecting emotion of an individual through facial expression and playing music according to the mood detected that will alleviate the mood or simply calm the individual and can also get quicker song according to the mood, saving time from looking up different songs and parallel developing a software that can be used anywhere with the help of providing the functionality of playing music according to the emotion detected. By developing a recommendation system, it could assist a user to make a decision regarding which music one should listen to helping the user to reduce his/her stress levels. The user would not have to waste any time in searching or to look up for songs and the best track matching the user's mood is detected, and songs would be shown to the user according to his/her mood. The image of the user is captured with the help of a webcam. The user's picture is taken and then as per the mood/emotion of the user an appropriate song from the playlist of the user is shown matching the user's requirement.

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2021

Every individual human might have completely different faces; however, their expressions tell us the same story and it notably plays a significant role in extraction of an individual’s emotions and behavior. Music is the purest form of art and a medium of expression, which is known to have a greater connection with a person’s emotions. It has a novel ability to lift one’s mood. This project system focuses on building an efficient music player which works on emotion of user using facial recognition techniques. The facial features extracted will generate a system thereby reducing the effort and time involved in doing it manually. Facial data is captured by employing a camera. The emotion module makes use of deep learning techniques to spot the exact mood relative to that expression. The accuracy of mood detection module in the system for real time footage is above 80%; while for static pictures it is 95 to one hundred percent. Therefore, it brings out higher accuracy relating to time and performance.

International Journal for Research in Applied Science and Engineering Technology IJRASET, 2020

The human face is an important organ of the human body and plays a major role in transmitting the individual's emotional and emotional state. Extremely isolating a song list and producing an appropriate playlist based on individual spiritual qualities is a very tiring, time-consuming, hard-working, and energetic activity. Various algorithms have been proposed and developed to facilitate the playlist implementation process. However the proposed algorithms available for implementation are slow, extremely precise and sometimes require the use of additional equipment such as EEG or sensors. This proposed model based on a facelifted model will generate playlists automatically thereby reducing the effort and time involved in handing over the process. Thus the proposed system tends to reduce the amount of time involved in obtaining the results and the total cost of the system, thereby increasing the accuracy of the entire program.

IRJET, 2020

International Journal of Engineering Research and Technology (IJERT), 2018

https://www.ijert.org/review-on-facial-expression-based-music-player https://www.ijert.org/research/review-on-facial-expression-based-music-player-IJERTCONV6IS15116.pdf Human often use nonverbal cues such as hand gestures, facial expressions, and tone of the voice to express feelings in interpersonal communications. The face of the human is an important organ of an individual's body and it plays an important role in extraction of an individual's behavior and emotional state. Facial expression provides current mind state of person. It is very time consuming and difficult to create and manage large playlists and to select songs from these playlists. Thus, it would be very helpful if the music player itself selects a song according to the current mood of the user. Manually segregating the list of songs associated, generating acceptable playlist supported an individual's emotions could be a terribly tedious, time overwhelming, intensive and upheld task Thus, an application can be developed to minimize these efforts of managing playlists. However the proposed existing algorithms in use are computationally slow and less accurate. This proposed system based on facial expression extracted will generate a playlist automatically thereby reducing the effort and time involved in rendering the process manually. Facial expressions are given using inbuilt camera. The image is captured using camera and that image is passed under different stages to detect the mood or emotion of the user. We will study about how to automatically detect the mood of the user and present him a playlist of songs which is suitable for his current mood. Proposed paper has used Viola-Jones algorithm and multiclass SVM (Support Vector Machine) for face detection and emotion detection respectively.

International journal of Emerging Trends in Science and Technology, 2016

The most recognizable part of a human body is the human face itself. The human face also plays an extremely significant role in extraction of an individual's current emotional state. Music can definitely be a mood changer, but manually segregating the list of songs and creating playlists according to the individual's emotional state can be very exhaustive, time consuming, boring and labour intensive work. To automate the playlist generation as well as saving humans from a lot of boring hardship a number of algorithms have been proposed as well as developed. However these algorithms have their own drawbacks, they are computationally very slow, less accurate and some of them even require additional hardware like EEG, sensors etc. which can obviously add up to the overall cost. Through this paper we propose a system based on facial expression extraction which would automate the process of playlist generation thereby reducing the effort as well as time required to segregate the list of songs. And moreover the proposed system tends to reduce the computational time in obtaining the results, improving the overall accuracy as well as reducing the designing cost too.

2021

The human face is an important part of an individual's body and extracting the required input from the human face can now be done directly using a camera. One of the applications of this input can be for extracting the information to deduce the mood of an individual. This data can then be used to get a list of songs that comply with the mood derived from the input provided earlier. This eliminates the time-consuming and tedious task of manually segregating or grouping songs into different lists and helps in generating an appropriate playlist based on an individual's emotional features. Various algorithms have been developed and proposed for automating the playlist generation process. The expressions of a person are detected by extracting the facial features using the HAAR classifier and Fisherface algorithm. The results show that the proposed system achieves up to 88.82% of accuracy level in recognizing the expressions.