Pitch Estimation Based on Long Frame Harmonic Model and Short Frame Average Correlation Coefficient

We propose a pitch estimation method based on long frame harmonic model (LFHM) and short frame average correlation coefficient (SFACC). The long frame used here is three times as long as the short frame. Our approach consists of two main steps: pitch candidates extraction based on LFHM, and final pitch selection based on the SFACC. The long frame analysis for speech signal is able to achieve a higher harmonic resolution and ensures the inclusion of the true pitch in the pitch candidate pool. The SFACC based pitch selection method is robust to noise and keeps the short-time stationary features of speech. Experimental results show that our method outperforms several state-of-the-art algorithms under both clean and noisy acoustic environments.