International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 10 Issue: 08 | Aug 2023
p-ISSN: 2395-0072
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Mood Sensitive Music Recommendation System T Sunil Kumar1, CH Harshitha2, G Naga Charani3, MD Nawaz4 , G Nithin5 1 Professor, VNR Vignana Jyothi Institute of Engineering & Technology, Hyderabad 2345Under Graduate Student, VNR Vignana Jyothi Institute of Engineering & Technology, Hyderabad
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Abstract - The mood sensitive music recommendation
music recommendation systems and how the proposed Mood Music Recommendation System addresses these issues. We will discuss the potential applications and future directions of the Mood Music Recommendation System, highlighting the possibilities for integrating it into music streaming platforms, mobile applications, and other musicrelated services.
system using facial expressions is a system designed to provide music recommendations based on the user's current mood as inferred from their facial expressions. The system uses computer vision and machine learning algorithms to analyze the user’s facial expressions in real time such as using webcam. The system then recommends music that matches the user’s mood considering the tempo and genre of the music. Once the user's current emotional state has been determined, the system then selects music that is likely to match that mood. For example, if the user is determined to be feeling sad, the system might recommend slower, more melancholic music, while if the user is determined to be feeling happy, the system might recommend more upbeat and energetic music. The system may be applied in a number of situations, like music streaming services or in retail environments where music is played to create a particular atmosphere. By tailoring the music to the user's current mood, the system aims to provide a more personalized and enjoyable listening experience. Also, improves their emotional state.
We will also reflect on the ethical considerations associated with personalized recommendation systems and explore avenues for addressing privacy concerns and ensuring fair usage. The Mood Music Recommendation System offers a novel approach to enhance the music listening experience by providing tailored recommendations based on the user's mood. This project report will serve as a comprehensive guide, shedding light on the design, implementation, and evaluation of the system, and laying the foundation for further advancements in the field of intelligent music recommendation. The purpose of this study is to develop a music recommendation system that can recognise a user's face, determine their current mood, and then suggest a playlist depending on that mood.
Key Words: (Facial Detection, Emotion detection, Music Recommendation, CNN.)
2. LITERATURE SURVEY
1.INTRODUCTION
2.1. Music Emotion Recognition: A State of the Art Review (2011)
Music has the remarkable ability to evoke emotions, influence moods, and connect with our inner selves. Whether it's to lift our spirits, relax our minds, or accompany specific activities, music plays an integral role in our daily lives. However, with the vast array of musical genres and artists available today, finding the perfect song that resonates with our current mood can be a daunting task. This is where the Mood Music Recommendation System comes into play.
Yang and Chen's review paper offers an extensive analysis of music emotion recognition techniques. It explores the different modalities used to capture emotion, including audio features, lyrics, and user feedback. The paper discusses the various machine learning algorithms employed for emotion classification, such as support vector machines (SVM), decision trees, and artificial neural networks. It highlights the importance of feature selection and extraction in improving the accuracy of emotion recognition systems. Additionally, the review discusses the challenges faced in music emotion recognition, such as subjectivity and the inherent complexity of emotional experiences. The authors present future directions for research, including the integration of multi-modal information and the exploration of deep learning approaches to enhance music emotion recognition systems.
The Mood Music Recommendation System is an innovative application of artificial intelligence and machine learning techniques that aims to enhance the music listening experience by providing personalized music recommendations based on the user's mood. By analyzing various audio features, lyrics, and user preferences, the system can effectively understand and categorize music according to its emotional content. We will explore the existing challenges and limitations faced by conventional
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