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Lyrics-Conditioned Neural Melody Generation

机译:歌词条件下的神经旋律生成

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Generating melody from lyrics to compose a song has been a very interesting research topic in the area of artificial intelligence and music, which tries to predict generative music relationship between lyrics and melody. In this demonstration paper, by exploiting a large music dataset with 12,197 pairs of English lyrics and melodies, we develop a lyrics-conditioned AI neural melody generation system that consists of three components: lyrics encoder network, melody generation network, and MIDI sequence tuner. Most importantly, a Long Short-Term Memory (LSTM)-based melody generator conditioned on lyrics, is trained by applying a generative adversarial network (GAN), to generate a pleasing and meaningful melody matching the given lyrics. Our demonstration illustrates the effectiveness of the proposed melody generation system.
机译:从歌词产生旋律以构成歌曲一直是人工智能和音乐领域中非常有趣的研究课题,它试图预测歌词与旋律之间产生的音乐关系。在此演示文件中,通过利用包含12197对英语歌词和旋律的大型音乐数据集,我们开发了一种基于歌词的AI神经旋律生成系统,该系统由三个组件组成:歌词编码器网络,旋律生成网络和MIDI序列调谐器。最重要的是,通过应用生成对抗网络(GAN)来训练以歌词为条件的基于长短期记忆(LSTM)的旋律生成器,以生成与给定歌词匹配的令人愉悦且有意义的旋律。我们的演示说明了所提出的旋律生成系统的有效性。

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