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.

提出了一种深度注意力对齐网络，旨在以类似于人类音乐创作的方式，通过给定的不完整歌词来自动预测歌词和旋律。文章中探索了深度神经网络从歌词到旋律的编码和解码方式，并利用注意力机制在歌词到旋律生成过程中对齐预测的歌词和旋律。定量及定性评价表明，所提出的方法确实能够为给定不完整的种子歌词创作出适当的歌词和相应的旋律。