基于情感的情绪增强音乐推荐

Aurobind V. Iyer, Viral Pasad, Smita Sankhe, Karan D. Prajapati
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引用次数: 27

摘要

音乐是最有效的媒介之一,因为它可以灌输深刻的感情,让听众沉浸在潜意识的信息中。它巧妙地玩弄我们的情绪,从而影响我们的情绪。书籍、电影和电视剧是其他几种媒介,但与这些相比,音乐在短短几分钟内传递信息。当我们情绪低落时,它可以帮助我们,给我们力量。当我们听悲伤的歌曲时,我们往往会感到情绪低落。当我们听快乐的歌曲时,我们感到更快乐。根据心情对歌曲进行人工分类,制作播放列表,既耗时又费力。我们的论文提出了一个名为“EmoPlayer”的系统,这是一个Android应用程序,它可以根据用户当前的情绪向用户推荐一份歌曲列表,从而最大限度地减少这些努力。该系统使用摄像头捕捉用户的图像并检测其面部。然后,它会检测到他的情绪,并列出一个歌曲列表,随着歌曲的播放,这些歌曲会提高他的情绪。EmoPlayer使用Viola Jones算法进行人脸检测,使用Fisherfaces分类器进行情绪分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Emotion based mood enhancing music recommendation
Music is one of the most effective media as it can instill deep feelings and swamp listeners with subliminal messages. It deftly plays with our emotions which in turn affect our mood. Books, movies and television dramas are a few other media but, in contrast to these, music delivers its message in mere moments. It can aid us when we are feeling low and empower us. When we listen to sad songs, we tend to feel a decline in mood. When we listen to happy songs, we feel happier. Manual classification of songs based on mood, for making of a playlist, is time consuming and labour intensive. Our paper proposes a system ‘EmoPlayer’, an Android application, which help to minimize these efforts by suggesting the user a list of songs based on his current emotion. The system captures user's image using camera and detects his face. It then detects the emotion and makes a list of songs which will enhance his mood as the songs keep playing. EmoPlayer uses Viola Jones algorithm for face detection and Fisherfaces classifier for emotion classification.
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