Instantaneous fundamental frequency estimation of speech signals using tunable-$Q$ wavelet transform
Anurag Nishad, Ram Bilas Pachori · 2018
This paper presents a novel method to estimate the instantaneous fundamental frequency (IFF) of speech signals using tunable-Q wavelet transform (TQWT). The proposed method uses a TQWT based filter-bank which has common or nearly uniform bandwidth for all sub-bands. This filter-bank is used to decompose the speech signal. The fundamental frequency component (FFC) of speech signal may be present in many subbands at different time intervals. The time interval at where FFC is present, in a sub-band, is identified using time-domain segmentation (TDS) section. In the similar way, the harmonic of FFC can also be present in different sub-bands at different time durations. The proposed method extracts FFC from different sub-bands and constructs a FFC for entire speech signal. Then, Hilbert transform is applied on constructed FFC to obtain IFF of speech signal. In order to show the efficacy of proposed method, it's performance has been compared with performance of other existing methods in terms of gross error in percentage.