A multi-scale fully convolutional network for singing melody extraction

Ping Gao, Cheng You You, Tai-Shih Chi

研究成果: Conference contribution同行評審

7 引文 斯高帕斯(Scopus)

摘要

The melody extraction can be considered as a se-quence-to-sequence task or a classification task. Many recent models based on semantic segmentation have been proven very effective in melody extraction. In this paper, we built up a fully convolutional network (FCN) for melody extraction from polyphonic music. Inspired by the state-of-the-art architecture of the semantic segmentation, we constructed the encoder in a dense way and designed the decoder accordingly for audio processing. The combined frequency and periodicity (CFP) representation, which contains spectral and cepstral information, was adopted as the input feature of the proposed model. We conducted performance comparison between the proposed model and several methods on various datasets. Experimental results show the proposed model achieves state-of-the-art performance with less computation and fewer parameters.

原文English
主出版物標題2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019
發行者Institute of Electrical and Electronics Engineers Inc.
頁面1288-1293
頁數6
ISBN(電子)9781728132488
DOIs
出版狀態Published - 11月 2019
事件2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019 - Lanzhou, China
持續時間: 18 11月 201921 11月 2019

出版系列

名字2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019

Conference

Conference2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019
國家/地區China
城市Lanzhou
期間18/11/1921/11/19

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