Abstract
We propose a deep attention-based alignment network, which aims to automatically predict lyrics and melody with given incomplete lyrics as input in a way similar to the music creation of humans. Most importantly, a deep neural lyrics-to-melody net is trained in an encoder-decoder way to predict possible pairs of lyrics-melody when given incomplete lyrics (few keywords). The attention mechanism is exploited to align the predicted lyrics with the melody during the lyrics-to-melody generation. The qualitative and quantitative evaluation metrics reveal that the proposed method is indeed capable of generating proper lyrics and corresponding melody for composing new songs given a piece of incomplete seed lyrics.
Abstract (translated)
我们提出了一种基于深度注意力的对齐网络,该网络旨在以类似于人类音乐创作的方式,使用给定不完整歌词作为输入,自动预测歌词和旋律。最重要的是,一种深度神经网络的歌词到旋律网络被训练以编码和解码时序数据,在给定不完整歌词的情况下预测可能的歌词旋律对(几个关键词)。注意力机制被利用在歌词到旋律的生成过程中,以将预测的歌词与旋律对齐。定性和定量评估指标表明, proposed 方法确实能够生成正确歌词和对应的旋律,以基于不完整种子歌词创作新的歌曲。
URL
https://arxiv.org/abs/2301.10015
