Song Recommendation System Based on Real-Time Facial Expressions

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.

International Journal for Research in Applied Science & Engineering Technology (IJRASET), 2022

The study of human emotional responses to visual stimuli such as photos and films, known as visual sentiment analysis, has proven a fascinating and difficult problem. It attempts to comprehend the high-level information of visual data. The development of strong algorithms from computer vision is responsible for the present models' success. The majority of existing models attempt to overcome the problem by recommending either robust features or more sophisticated models. Visual elements from the entire image or video are the key proposed inputs in particular. Local areas have received less attention, which we believe is important to the emotional reaction of humans to the entire image. Image recognition is used to locate people in photos, analyse their emotions, and play emotion-related tunes based on their feelings. This repo accomplishes this goal by utilising the Google platform's Vision services. Given an image, it would look for faces, identify them, draw a rectangle around them, and describe the emotion it discovered.

mantech publications, 2023

Music is the mirror of one's emotion. In simple words, we can say that music relates to a person's state of emotion or mood. We observe that some new technology and new methods are arising every day, and competing to this, we have proposed a music player based on the user's emotion through facial expression. Emotion can be recognized from a person's face easily by others. What if we can implement this method (i.e. emotion detection) on a machine?. We have developed an application that detects emotion through the machine's webcam and displays the set of songs commonly said as playlists based on emotion. Here, in this paper, we have used CNN classifier for neural network model and OpenCV to detect faces and train model to detect emotion.

International Journal for Research in Applied Science and Engineering Technology

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.

IRJET, 2021

Facial expression is one of the most difficult and highly convoluted procedures that have been undertaken in the image processing paradigm. Facial expression can be used for other purposes such as recognizing a person's mood as humans convey most of their emotions through their facial expressions. Identification of a person's mood is one of the most useful implementations as it can be used in various applications to improve the quality of life for an individual. Therefore, for this purpose, there has been an extensive analysis of the related works in this survey article for the purpose of reaching our approach for song recommendation through the mood analysis of the individual. Our prescribed approach utilizes convolutional neural networks along with fuzzy classification for effective song recommendation. This approach will be expanded in future research articles on this topic.

IRJET, 2022

Human facial expressions convey a lot of information visually rather than articulately. Facial expression recognition plays a very crucial role in the area of human- machine interaction.Face recognition technology has many applications, but they are generally limited to the understanding of human behavior, the detection of mental disorders, and synthesizing human expressions. This project aims to apply various deep learning methods to identify the seven key emotions: happiness, sadness, disgust, anger, fear, surprise, and neutrality, as well as suggest some mood booster songs

IRJET, 2021

Human emotions play a crucial role in analyzing the mood of an individual. Emotions of a person could be understood through various features of the face such as eyes, cheeks, or even through the smile on the face. Music is an art form that helps an individual to calm their body and brain. Our project deals with the blending of emotions and music. The proposed system detects the emotions of the individual through facial expressions and plays the music according to the mood detected. The expressions of the face could be happy, sad, angry, neutral, etc. The emotions on the face can be detected and captured through a webcam or an inbuilt camera. The emotions of an individual from the captured image could be detected using Fisherface Algorithm. Once the emotion is recognized, the system suggests a playlist for that emotion and plays the music automatically.

International Journal for Research in Applied Science & Engineering Technology (IJRASET), 2024

Music plays a significant role in improving and elevating one's mood as it is one of the important source of entertainment and inspiration to move forward. Recent studies have shown that humans respond as well as react to music in a very positive manner and that music has a high impact on human's brain activity. Now a days, people often prefer to listen to music based on their moods and interests. This work focuses on a system that suggests songs to the users, based on their state of mind. In this system, computer vision components are used to determine the user's emotion through facial expressions. Once the emotion is recognized, the system suggests a song for that emotion, saving a lot of time for a user over selecting and playing songs manually. Conventional method of playing music depending upon the mood of a person requires human interaction. Migrating to the computer vision technology will enable automation of such system. To achieve this goal, an algorithm is used to classify the human expressions and play a music track as according to the present emotion detected. It reduces the effort and time required in manually searching a song from the list based on the present state of mind of a person. The expressions of a person are detected by extracting the facial features using the HaarCascade algorithm and CNN Algorithm. An inbuilt camera is used to capture the facial expressions of a person which reduces the designing cost of the system as compared to other methods

International Journal for Research in Applied Science & Engineering Technology (IJRASET), 2022

In the day to day life of a human and in the technologies that is emerging, music is incredibly significant. Conventionally, it is the work of a user to search for a song manually from the list of songs in a music player. Here, an efficient and accurate model is introduced to generate a playlist on the basis of users present emotional state and behaviour. Existing methods for automated playlist building are computationally inefficient, inaccurate, and can involve the usage of additional gear such as EEG or sensors. Speech is the most primitive and natural form of communicating feelings, emotions, and mood, and its processing is computationally intensive, time-consuming, and expensive. This suggested system uses real-time face emotion extraction as well as audio feature extraction.