我们提出了一种有效的体系结构，可以检测MTG-Jamendo数据集的自动标记心情主题子集上音乐曲目中的心情/主题。我们的方法包括两个模块，一个是基于MobileNetV2架构的CNN模块，另一个是来自Transformer架构的自我关注模块，用于捕获长期时间特征。..

Music theme recognition using CNN and self-attention

We present an efficient architecture to detect mood/themes in music tracks on autotagging-moodtheme subset of the MTG-Jamendo dataset. Our approach consists of two blocks, a CNN block based on MobileNetV2 architecture and a self-attention block from Transformer architecture to capture long term temporal characteristics.We show that our proposed model produces a significant improvement over the baseline model. Our model (team name: AMLAG) achieves 4th place on PR-AUC-macro Leaderboard in MediaEval 2019: Emotion and Theme Recognition in Music Using Jamendo.