Frequency-Temporal Attention Network for Singing Melody Extraction

Autor:	Yu, Shuai, Sun, Xiaoheng, Yu, Yi, Li, Wei
Rok vydání:	2021
Předmět:	Computer Science - Sound Electrical Engineering and Systems Science - Audio and Speech Processing
Druh dokumentu:	Working Paper
DOI:	10.1109/LSP.2021.3080625
Popis:	Musical audio is generally composed of three physical properties: frequency, time and magnitude. Interestingly, human auditory periphery also provides neural codes for each of these dimensions to perceive music. Inspired by these intrinsic characteristics, a frequency-temporal attention network is proposed to mimic human auditory for singing melody extraction. In particular, the proposed model contains frequency-temporal attention modules and a selective fusion module corresponding to these three physical properties. The frequency attention module is used to select the same activation frequency bands as did in cochlear and the temporal attention module is responsible for analyzing temporal patterns. Finally, the selective fusion module is suggested to recalibrate magnitudes and fuse the raw information for prediction. In addition, we propose to use another branch to simultaneously predict the presence of singing voice melody. The experimental results show that the proposed model outperforms existing state-of-the-art methods. Comment: This paper has been accepted by ICASSP 2021
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2102.09763 Zobrazit plný text záznamu View this record from Arxiv