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Title: 基於 GRU 生成音樂
The Application of GRU to Generate Music
Authors: 賴晨心
Lai, Chen-Hsin
Contributors: 蔡瑞煌

Tsaih, Rua-Huan
Han, Tzu-Shian

Lai, Chen-Hsin
Keywords: 人工智慧
Neural networks
Music generation
Date: 2021
Issue Date: 2021-09-02 15:59:35 (UTC+8)
Abstract: 儘管從直覺上講,透過適當安排好的輸入/輸出變數表示和 GRU 模型 (Cho 等人,2014a )的超參數能夠學習巴赫和斯卡拉蒂鋼琴音樂來生成音樂,但文獻上仍沒有這樣的學術和實際試驗。本研究接受此挑戰,並設計相關實驗來了解是否能利用 GRU 模型學習巴赫和斯卡拉蒂鋼琴音樂後生成音樂。本研究採用基於節拍的事件數據表示(Huang 和 Yang,2020),並使用不同的輸入/輸出變數表示進行實驗。而在推理階段,我們將 GRU 模型的每個輸出序列連接起來並轉換回 MIDI 文件,從而生成音樂。實驗結果顯示了應用 GRU 生成音樂的正面性。
Although, intuitively, a proper arrangement of input/output presentation and hyperparameters of the state-of-the-art GRU model (Cho et al., 2014a) is capable of learning Bach and Scarlatti piano music and generating the music, there are no such academic and practical trials. This study addresses the challenge of generating music from learning Bach and Scarlatti piano music through the GRU model. This study employs the beat-based event data representation (Huang and Yang, 2020) and conducts an experiment with different input/output representations. As to the inferencing stage, each output sequence of the GRU model is concatenated and transformed back into a MIDI file, so that the music is generated. The experiment shows a positive result regarding the application of GRU to generate music.
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