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Image to Music: Cross-Modal Melody Generation Through Image Captioning

Goularas, Dionysis

Preprint | 2023 | Yeditepe University Academic and Open Access Information System

Advances in machine learning in recent years have also been seen in computationally creative systems. Interest in machine-generated artifacts paved a way for creative models to evolve as such. But the earlier methods mostly explored a one domain approach and cross-modal learning has stayed relatively unexplored. Thus, the direct mapping between modalities for cross-modal creative models is not fully explored. This work proposes a novel methodology for generating symbolic music through images by directly mapping their features. A CNN encoder and deepstacked LSTM decoder are the base models as the proposed method uses the image capti . . .oning approach to map the two domains’ features. The generated music is evaluated quantitatively by using a custom genre classification model and BLEU scores calculations. The qualitative evaluation involves a melody listening test with human evaluators. The results show that the proposed method works well for music generation Daha fazlası Daha az

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