This paper introduces Track Mix, a personalized playlist generation system released in 2022 on the music streaming service Deezer. Track Mix automatically generates "mix" playlists inspired by initial music tracks, allowing users to discover music similar to their favorite content. To generate these mixes, we consider a Transformer model trained on millions of track sequences from user playlists. In light of the growing popularity of Transformers in recent years, we analyze the advantages, drawbacks, and technical challenges of using such a model for mix generation on the service, compared to a more traditional collaborative filtering approach. Since its release, Track Mix has been generating playlists for millions of users daily, enhancing their music discovery experience on Deezer.

翻译：本文介绍Track Mix，一个于2022年在音乐流媒体服务Deezer上发布的个性化播放列表生成系统。Track Mix通过初始曲目启发自动生成"混合"播放列表，使用户能够发现与其喜爱内容相似的音乐。为生成这些混合列表，我们采用了一个在数百万用户播放列表的曲目序列上训练的Transformer模型。鉴于近年来Transformer日益流行，我们分析了在服务中使用该模型进行混合生成相较于传统协同过滤方法的优势、局限及技术挑战。自发布以来，Track Mix每天为数百万用户生成播放列表，增强了他们在Deezer上的音乐发现体验。