论文标题
基于性能事件向量和BRNN的旋律分类
Melody Classification based on Performance Event Vector and BRNN
论文作者
论文摘要
我们提出了一个音乐与技术会议（CSMT2020）的模型，该模型的旋律分类挑战。我们的模型使用性能事件向量作为输入序列，以构建用于分类的双向RNN网络。该模型在开发数据集和Wikifonia数据集上实现了令人满意的性能。我们还讨论了几个超参数的效果，并为评估数据集创建了多个预测输出。
We proposed a model for the Conference of Music and Technology (CSMT2020) data challenge of melody classification. Our model used the Performance Event Vector as the input sequence to build a Bidirectional RNN network for classfication. The model achieved a satisfying performance on the development dataset and Wikifonia dataset. We also discussed the effect of several hyper-parameters, and created multiple prediction outputs for the evaluation dataset.
