As artificial intelligence becomes more and more ingrained in daily life, we present a novel system that uses deep learning for music recommendation and emotion-based detection. Through the use of facial recognition and the DeepFace framework, our method analyses human emotions in real-time and then plays music that reflects the mood it has discovered. The system uses a webcam to take pictures, analyses the most common facial expression, and then pulls a playlist from local storage that corresponds to the mood it has detected. An engaging and customised experience is ensured by allowing users to manually change the song selection via a dropdown menu or navigation buttons. By continuously looping over the playlist, the technology guarantees continuity. The objective of our system is to improve emotional well-being through music therapy by offering a responsive and automated music-selection experience.

翻译：随着人工智能日益融入日常生活，我们提出了一种利用深度学习进行音乐推荐和基于情感检测的新型系统。通过采用面部识别技术和DeepFace框架，我们的方法能够实时分析人类情感，随后播放与所识别情绪相匹配的音乐。该系统通过摄像头采集图像，分析最普遍的面部表情特征，继而从本地存储中调取与检测情绪相对应的播放列表。用户可通过下拉菜单或导航按钮手动调整曲目选择，从而确保获得具有吸引力的个性化体验。该技术通过持续循环播放列表来保证音乐的连贯性。本系统的目标是通过提供响应式自动音乐选择体验，借助音乐疗法提升使用者的情绪健康水平。