Abstract
Lyrics take a great role to express users’ feelings. Every user has its own patterns and styles of songs. This paper proposes a method to capture the patterns and styles of users and generates lyrics automatically, using Long Short-Term Memory network combined with language model. The Long Short-Term memory network can capture long-term context information into the memory, this paper trains the context representation of each line of lyrics as a sentence vector. And with the recurrent neural network-based language model, lyrics can be generated automatically. Compared to the previous systems based on word frequency, melodies and templates which are hard to be built, the model in this paper is much easier and fully unsupervised. With this model, some patterns and styles can be seen in the generated lyrics of every single user.
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Acknowledgement
This paper is supported by the Science and Technology Commission of Shanghai Municipality (16511102400), by Innovation Program of Shanghai Municipal Education Commission (14YZ024), and by the Jiangsu Key Laboratory of Image and Video Understanding for Social Safety (Nanjing University of Science and Technology), Grant No. 30920140122007.
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Wu, X., Du, Z., Zhong, M., Dai, S., Liu, Y. (2017). Chinese Lyrics Generation Using Long Short-Term Memory Neural Network. In: Benferhat, S., Tabia, K., Ali, M. (eds) Advances in Artificial Intelligence: From Theory to Practice. IEA/AIE 2017. Lecture Notes in Computer Science(), vol 10351. Springer, Cham. https://doi.org/10.1007/978-3-319-60045-1_43
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