Frame Length Dependency for Fundamental Frequency Extraction in Noisy Speech ()
ABSTRACT
The fundamental frequency plays a significant part in understanding and
perceiving the pitch of a sound. The pitch is a fundamental attribute employed
in numerous speech-related works. For fundamental frequency extraction, several
algorithms have been developed which one to use relies on the signal’s
characteristics and the surrounding noise. Thus, the algorithm’s noise
resistance becomes more critical than ever for precise fundamental frequency
estimation. Nonetheless, numerous state-of-the-art algorithms face struggles in achieving satisfying outcomes when
confronted with speech recordings that are noisy with low signal-to-noise ratio
(SNR) values. Also, most of the recent techniques utilize different
frame lengths for pitch extraction. From this point of view, This research
considers different frame lengths on male and female speech signals for
fundamental frequency extraction. Also, analyze the frame length dependency on
the speech signal analytically to understand which frame length is more
suitable and effective for male and female speech signals specifically. For the
validation of our idea, we have utilized the conventional autocorrelation
function (ACF), and state-of-the-art method BaNa. This study puts out a potent
idea that will work better for speech processing applications in noisy speech.
From experimental results, the proposed idea represents which frame length is
more appropriate for male and female speech signals in noisy environments.
Share and Cite:
Rahman, M. , Chowdury, A. , Parvin, N. , Saha, A. and Rahman, M. (2024) Frame Length Dependency for Fundamental Frequency Extraction in Noisy Speech.
Journal of Signal and Information Processing,
15, 1-17. doi:
10.4236/jsip.2024.151001.
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