Weighted autocorrelation for pitch extraction of noisy speech

2001 ◽  
Vol 9 (7) ◽  
pp. 727-730 ◽  
Author(s):  
T. Shimamura ◽  
H. Kobayashi
Keyword(s):  
Noisy Speech ◽  
Pitch Extraction

scholarly journals Windowless-Autocorrelation-Based Cepstrum Method for Pitch Extraction of Noisy Speech

2012 ◽  
Vol 16 (3) ◽  
pp. 231-239 ◽  
Author(s):  
M. A. F. M. Rashidul Hasan ◽  
M. Shahidur Rahman ◽  
Tetsuya Shimamura
Keyword(s):  
Noisy Speech ◽  
Pitch Extraction

Research on Pitch Extraction Algorithm of Noisy Speech

2012 ◽  
Vol 433-440 ◽  
pp. 4675-4678
Author(s):  
Hong Yan Xing ◽  
Cui Hua Yu ◽  
Peng Li
Keyword(s):  
Speech Signal ◽  
Signal To Noise Ratio ◽  
Pitch Detection ◽  
Noisy Environment ◽  
Pitch Period ◽  
Noisy Speech ◽  
Hilbert Huang Transform ◽  
Extraction Algorithm ◽  
Soft Threshold ◽  
Pitch Extraction

Pitch detection in noisy environment plays an important role in speech analyzing and recognition. In the light of the properties of Hilbert-Huang transform and the EMD soft-threshold de-noising method, an effective pitch detection method for noisy speech signal is proposed in this paper. Firstly, the EMD soft-threshold de-noising method is applied to realize the background noise reduction, secondly, using the Hilbert-Huang transform to detect the pitch period of the de-noising speech signal. The analysis proposed in this paper show that, compared with the conventional methods of the pitch detection of the noisy speech, especially for the low signal to noise ratio (SNR), this approach has a higher accuracy.

scholarly journals Pitch Extraction Using Fourth-Root Spectrum in Noisy Speech

2020 ◽  
Vol 24 (5) ◽  
pp. 207-222
Author(s):  
Md. Saifur Rahman ◽  
Yosuke Sugiura ◽  
Tetsuya Shimamura
Keyword(s):  
Noisy Speech ◽  
Fourth Root ◽  
Pitch Extraction

Multi-resolution Gammachirp Envelope Distortion Index for Intelligibility Prediction of Noisy Speech

2018 ◽  
Author(s):  
Katsuhiko Yamamoto ◽  
Toshio Irino ◽  
Narumi Ohashi ◽  
Shoko Araki ◽  
Keisuke Kinoshita ◽  
...  
Keyword(s):  
Noisy Speech ◽  
Distortion Index
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