Threshold Filtering for Phoneme Pronunciation Signals Based on FrFT
- Resource Type
- Conference
- Authors
- Fan, Zhenyan; Yu, Jun; Li, Zhongxiao; Zhuang, Xiaodong; Mastorakis, Nikos E.
- Source
- 2018 2nd European Conference on Electrical Engineering and Computer Science (EECS) EECS Electrical Engineering and Computer Science (EECS),2018 2nd European Conference on. :118-122 Dec, 2018
- Subject
- Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Fields, Waves and Electromagnetics
Robotics and Control Systems
Signal Processing and Analysis
Europe
Electrical engineering
Computer science
FrFT
Weighted Variance
Threshold Filtering
SNR
- Language
The Fractional Fourier Transform (FrFT) is applied to the denoising of noisy speech. The optimal transform order of FrFT for single phoneme is determined by using weighted variance method. Then the soft-hard threshold compromise denoising algorithm is put forward. This method removes the amplitude of noise from noisy phoneme signals in FrFT-domain. Signals are reconstructed by inverse FrFT to get original speech. The experimental results show that this method can effectively remove noise from signals and get a good auditory effect, and this algorithm is of low computational complexity.