A Novel Pitch Detection Algorithm Based On Instantaneous Frequency
Zied Mnasri, Stefano Rovetta, Francesco Masulli · 2021 29th European Signal Processing Conference (EUSIPCO) · 2021
In this paper, a novel pitch detection algorithm (PDA) is presented. Though pitch detection is a classical problem that has been investigated since the very beginning of speech processing, the proposed algorithm is based on a novel approach relying on a proposed empirical relationship between fundamental frequency$(f_{0})$and instantaneous frequency$(f_{i})$. Basically,$f_{0}$is defined for periodic signals only, whereas$f_{i}$can be calculated for any type of signals using the Hilbert transform. Notwithstanding this substantial difference, the relationship described in this paper shows some interaction between them, at least empirically. Once this relationship was validated on a large set of speech signals, it has been exploited to implement an algorithm in order to (a) detect voiced parts of speech and (b) extract$f_{0}$contour from$f_{i}$pattern in the voiced regions. The obtained results of the proposed method were compared to those of some well-rated state-of-the-art PDA's of different backgrounds, to show that the quality of pitch detection yielded by the proposed approach is quite satisfactory, both in clean and simulated noisy speech.