Combining Zero Replacement Speech Enhancement with Lag Window Method for Pitch Detection
Sicong Du, Yosuke Sugiura, Tetsuya Shimamura · 2018
Pitch is one of the most essential features in human speech analysis. Although numerous pitch detection methods have been developed, it is still a challenge to provide a high pitch detection performance in noisy environments. In this paper, we propose an anti-noise pitch detection method that combines a speech enhancement algorithm with a spectral flattening algorithm. In the experiments, we compare the proposed method with several widely used or state-of-the-art pitch detection methods. The results show that the proposed method has the lowest gross pitch error (GPE) rate among all the methods when dealing with white-noise added male speeches. Moreover, comparing the pitches estimated by the proposed method to those estimated by the conventional lag window method, we can see that the speech enhancement algorithm helps diminish pitch errors.