Music2Vec:音乐类型分类和推荐系统

Aishwariya Budhrani, Akashkumar Patel, Shivam Ribadiya
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引用次数: 4

摘要

在当今世界,由于音乐曲目通过离线和在线的快速增长,并且提供更好的自动分类其类型的访问,并在此基础上推荐另一首歌曲将影响用户的良好体验。因此,本文提出了一个使用深度学习方法对歌曲进行类型分类的系统,并在此基础上使用word2vec进行歌曲推荐。对于分类,重要的是获得一个大的集合,并根据它们的类型对歌曲进行索引,并借助跳跃克模型,它将识别相似的上下文歌曲进行推荐。因此,所提出的系统作为一个完整的音乐推荐系统在用户端提供良好的体验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Music2Vec: Music Genre Classification and Recommendation System
In today’s world, due to the rapid growth in music tracks via both offline and online and give better access to automatically classify its genre and based on that the recommendation for another song will impact a great experience to the user. So, this paper has proposed a system that uses deep learning approach for performing genre classification on the song and based on that the song will be recommended by using word2vec. For classification, it is important to obtain a large collection and index the songs accordingly to their genre and with the help of skip gram model, it will identify the similar context song for recommendation. So, the proposed system works as a whole music recommendation system for delivering great experience at user side.
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