Symbolic Melody Phrase Segmentation Using Neural Network with Conditional Random Field
| Autor: | Gus Xia, Yixiao Zhang |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Structure (mathematical logic)
Melody Conditional random field Phrase Artificial neural network business.industry Computer science Machine learning computer.software_genre Data set ComputingMethodologies_PATTERNRECOGNITION Music information retrieval Segmentation Artificial intelligence business computer |
| Zdroj: | Proceedings of the 8th Conference on Sound and Music Technology ISBN: 9789811616488 |
| Popis: | Automatic melodic phrase detection and segmentation is a classical task of content-based music information retrieval and also a key problem of automatic music structure analysis. In this paper, we apply neural network architectures with conditional random field (CRF) to produce satisfactory melodic phrase segmentation. To tackle the problem of the sparse labelling problem of data, we design two tailored label-engineering techniques with corresponding training techniques for different neural networks. We compare the performance of the traditional model on the public data set Essen Folksong Database. The experimental results show that the performance of the model using the neural CRF architecture far exceeds that of the traditional method. The results of ablation experiments on Essen Folksong Database and POP909 dataset show that the improvement of performances mainly comes from the introduction of CRF structure. Besides, our labelling techniques also improve model performance and make training process more robust (Codes and data are available at https://github.com/ldzhangyx/music-melody-segmentation-using-neural-CRF). |
| Databáze: | OpenAIRE |
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