International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 10 Issue: 05 | May 2023
p-ISSN: 2395-0072
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Facial recognition to detect mood and recommend songs Syed Waheedulla, Prof.Harashleen Kour, Mulinti Meghanath Reddy, Sriramoju Nikhil Sai, Piyush Majumdar Department of computer science and engineering, Chandigarh University, Gharuwan, 140301,Punjab,India ---------------------------------------------------------------------***--------------------------------------------------------------------possibilities for providing a more personalized music Abstract—This research paper presents a experience. The aim of this research paper is to explore the concept of using facial recognition technology to accurately identify emotions and make song recommendations in accordance with the observed mood. This technology can potentially revolutionize the way we interact with machines and assist us in achieving emotional
development of a web-application with a facial recognition system that uses computer vision, algorithms and machine learning approaches to effectively determine a user’s emotions in real-time. The system interprets facial features such as the eyes, mouth, and forehead to detect emotions, including happiness, sadness, neutral, and rock. Based on the detected emotion and the selected language and singer, the system recommends songs that best fit the user’s mood and preferences. To train the deep learning model, FER-2013 dataset of labeled facial images is used. The system is implemented in realtime video input, providing personalized recommendations to the user based on their mood. The proposed system has the potential to revolutionize the way we listen to music and enhance our wellbeing. By providing personalized recommendations based on the user’s emotions and preferences, the system could improve the user’s music listening experience and mood. To evaluate the system’s performance we conducted experiments using a dataset of labeled facial images. The results showed that the system accurately detects emotions, with an average accuracy of 81conducted a user study to evaluate the system’s effectiveness in providing personalized recommendations. The results showed that the system was successful in providing recommendations that matched the user’s mood and preferences.
well-being.[1] Music has the power to influence our feelings and emotions, but with a vast music library available, it can be challenging to find the right music that matches our current emotional state. This is where facial recognition technology can play a crucial role. By analyzing facial expressions in real-time, the proposed system can detect the user’s mood accurately and employ machine learning algorithms to recognize different face characteristics associated with various emotions such as happiness, sadness, anger, surprise, and neutrality. By merging facial recognition technology and machine learning algorithms, the suggested system can create an efficient music recommendation system that can recognise the user’s mood and select music that matches it using facial recognition techniques. This personalised music experience has the potential to change the way people listen to music by making it more immersive and intriguing. The success of this experiment may encourage the development of comparable systems in other sectors, thereby broadening the capabilities of facial recognition technology. The purpose of this research paper is to provide a detailed review of the notion of applying facial recognition technology in the music industry, as well as insights into its possible influence on the music industry and beyond. Overall, the goal of this research article is to help design a more efficient and cost-effective facial recognition system that can recognise facial emotions and select songs based on the user’s mood.
Keywords—Facial Recognition Technology, Emotion
Recognition, Music Recommendation System, Vision, Machine Learning, Convolutional Neural Network, Mood Detection, Natural Language Processing, Deep Learning
1. INTRODUCTION
II. LITERATURE REVIEW
Facial recognition technology has gained immense popularity in recent years and has been widely used in various industries, including marketing, healthcare, and security.
Visnu Dharsini et al.[2] proposed a paper which discusses the potential of facial recognition technology in various fields and its ability to recognize a person’s emotions. It highlights the unique connection between music and emotions and proposes an efficient music recommendation system that uses facial recognition techniques to determine a user’s emotion. The paper
However, its potential in the music industry remains largely untapped. The ability to identify human emotions through facial expression analysis has opened up new
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