Fundamental frequency extraction by utilizing modified BaNa in noisy speech

Abstract

A sound’s pitch can be largely understood and perceived by using its fundamental frequency. Multiple algorithms have been developed for extracting fundamental frequency, and the choice of which one to employ depends on the noise and features of the signal. Therefore, for an accurate fundamental frequency estimate, the noise resistance of the algorithm becomes even more crucial. Still, many of the most advanced algorithms fail to produce acceptable results when faced with loud speech recordings that have low signal-to-noise ratios (SNRs). In this research paper, we focus on the harmonic selection step in BaNa method, which is one of the vital parts for enhancing the extraction accuracy of fundamental frequency (F0) in noisy situations. BaNa algorithm always emphasizes 5 harmonics on average for both male and female speakers. However, our observation reveals that relying on 5 harmonics is inadequate for male speakers in noisy conditions. Thus, we propose a new idea based on BaNa that separately utilizes the 3 harmonics for male speakers and 5 harmonics for female speakers to achieve accurate pitch extraction within noisy environments. The results demonstrate that our proposed approach attains the lowest rate of gross pitch error (GPE) across various noise types and SNR levels.