Automatic Piano Harmony Arrangement System Based on Deep Learning. (25th July 2022)
- Record Type:
- Journal Article
- Title:
- Automatic Piano Harmony Arrangement System Based on Deep Learning. (25th July 2022)
- Main Title:
- Automatic Piano Harmony Arrangement System Based on Deep Learning
- Authors:
- Li, Jianhua
- Other Names:
- Li Yuan Academic Editor.
- Abstract:
- Abstract : Harmony, which plays an important role in enriching melody expression, is a combination of multiple notes. Melody coordination involves adding harmony effect to a single note of melody, which involves professional knowledge of basic music theory and harmony rules, and requires a high technical threshold. Under the macro background of deep learning and neural network technology, artificial intelligence is widely used in music retrieval, music creation, and music teaching. In this article, we provide a powerful tool for piano music creation by manually arranging melody and harmony instead of using deep learning. In this paper, harmonic elimination is divided into three subtasks: note detection, measurement, and multifundamental frequency estimation and model training. The music signal is divided into several segments by note detection, and the main notes and harmonic components of each segment are extracted by multifundamental frequency estimation, which are used as the features and labels of the neural network, so as to give a model with the ability of arrangement and harmony.
- Is Part Of:
- Journal of sensors. Volume 2022(2022)
- Journal:
- Journal of sensors
- Issue:
- Volume 2022(2022)
- Issue Display:
- Volume 2022, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 2022
- Issue:
- 2022
- Issue Sort Value:
- 2022-2022-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-07-25
- Subjects:
- Detectors -- Periodicals
681.205 - Journal URLs:
- https://www.hindawi.com/journals/js/ ↗
- DOI:
- 10.1155/2022/7662443 ↗
- Languages:
- English
- ISSNs:
- 1687-725X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 22959.xml