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Research on Automatic Music Recommendation Algorithm Based on Facial Micro-expression Recognition

机译:基于面部微表情识别的自动音乐推荐算法研究

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In recent years, with the development and application of big data, deep learning has received more and more attention. As a deep learning neural network, convolutional neural network plays an extremely important role in face image recognition. In this paper, a combination of micro-expression recognition technology of convolutional neural network and automatic music recommendation algorithm is developed to identify a model that recognizes facial micro-expressions and recommends music according to corresponding mood. The facial micro-expression recognition model established in this paper uses FER2013 with a recognition rate of 62.1%. After identifying the corresponding expression, a content-based music recommendation algorithm is used to extract the feature vector of the song and a cosine similarity algorithm is used to make the music recommendation. This research helps to improve the practicality of the music recommendation system, and the related results will also serve as a reference for the application of the music recommendation system in areas such as emotion regulation.
机译:近年来,随着大数据的开发和应用,深度学习受到越来越多的关注。卷积神经网络作为一种深度学习神经网络,在人脸图像识别中起着极其重要的作用。本文将卷积神经网络的微表情识别技术与自动音乐推荐算法相结合,开发了一种识别面部微表情并根据相应情绪推荐音乐的模型。本文建立的人脸微表情识别模型采用FER2013,识别率为62.1%。识别出相应的表达后,基于内容的音乐推荐算法用于提取歌曲的特征向量,并使用余弦相似度算法进行音乐推荐。该研究有助于提高音乐推荐系统的实用性,相关结果也将为音乐推荐系统在情绪调节等领域的应用提供参考。

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