Abstract
In this paper, we study a novel task that learns to compose music from natural language. Given the lyrics as input, we propose a melody composition model that generates lyrics-conditional melody as well as the exact alignment between the generated melody and the given lyrics simultaneously. More specifically, we develop the melody composition model based on the sequence-to-sequence framework. It consists of two neural encoders to encode the current lyrics and the context melody respectively, and a hierarchical decoder to jointly produce musical notes and the corresponding alignment. Experimental results on lyrics-melody pairs of 18,451 pop songs demonstrate the effectiveness of our proposed methods. In addition, we apply a singing voice synthesizer software to synthesize the “singing” of the lyrics and melodies for human evaluation. Results indicate that our generated melodies are more melodious and tuneful compared with the baseline method.
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A syllable is a word or part of a word which contains a single vowel sound and that is pronounced as a unit. Chinese is a monosyllabic language which means words (Chinese characters) predominantly consist of a single syllable (https://en.wikipedia.org/wiki/Monosyllabic_language).
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We calculate these metrics by scikit-learn with the parameter average set as ‘weighted’: http://scikit-learn.org/stable/modules/classes.html#module-sklearn.metrics.
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A singing voice synthesizer software which can synthesize Chinese song, http://www.dsoundsoft.com/product/niaoeditor/.
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Bao, H. et al. (2019). Neural Melody Composition from Lyrics. In: Tang, J., Kan, MY., Zhao, D., Li, S., Zan, H. (eds) Natural Language Processing and Chinese Computing. NLPCC 2019. Lecture Notes in Computer Science(), vol 11838. Springer, Cham. https://doi.org/10.1007/978-3-030-32233-5_39
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