Pitch Tracking Based on Statistical Anticipation
نویسندگان
چکیده
An effective multi-pitch tracking algorithm for noisy speech is critical for auditory processing. However, the performance of existing algorithms is not satisfactory. We have developed a robust algorithm for multi-pitch tracking of noisy speech based on statistical anticipation. By combining an improved channel and peak selection method, a new integration method for extracting periodicity information across the different channels, and a hidden Markov model (HMM) for forming continuous pitch tracks, our algorithm can reliably track single and double pitch tracks in a noisy environment.
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