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Lyrics-Conditioned Neural Melody Generation

机译:歌词条件神经旋律发电

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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:从歌词中产生旋律来组成一首歌是人工智能和音乐领域的一个非常有趣的研究主题,这试图预测歌词和旋律之间的生成音乐关系。在这篇演示论文中,通过利用12,197对英语歌词和旋律的大型音乐数据集,我们开发了一个由三个组件组成的歌词调节的AI神经熔体发电系统: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,通过应用生成的对冲网络(GaN)来训练在歌词上调节的长短期记忆(LSTM)的旋律发生器,以产生符合给定歌词的令人愉悦和有意义的旋律。我们的示范说明了所提出的熔融发电系统的有效性。

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