https://scholars.lib.ntu.edu.tw/handle/123456789/637188
Title: | Pitch Estimation by Denoising Preprocessor and Hybrid Estimation Model | Authors: | Hung, Yu Cheng PING-HUNG CHEN JIAN-JIUN DING |
Keywords: | fundamental frequency | music signal processing | pitch estimation | vocal signal enhancement | Issue Date: | 1-Jan-2023 | Source: | 2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023 - Proceedings | Abstract: | Pitch estimation is to estimate the fundamental frequency and the midi number and plays a critical role in music signal analysis and vocal signal processing. In this work, we proposed a new architecture based on a learning-based enhancement preprocessor and a combination of several traditional and deep learning pitch estimation methods to achieve better pitch estimation performance in both noisy and clean scenarios. We test 17 different types of noise and 4 SNRdb noise levels. The results show that the proposed pitch estimation can perform better in both noisy and clean scenarios with short response time. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/637188 | ISBN: | 9798350324174 | DOI: | 10.1109/ICCE-Taiwan58799.2023.10226907 |
Appears in Collections: | 電機工程學系 |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.