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A Review of Repetition Rate as Fundamental Frequency Extraction in Complex Voice Signals
Ingo R Titze1, Anil Palaparthi1
1Utah Center for Vocology, University of Utah, Salt Lake City, Utah.
Summary
Determining fundamental frequency (fo) is challenging with weak components or subharmonics. Algorithms often predict the greatest common divisor (GCD) as fo, but period-2 subharmonics can be misidentified.
Area of Science:
- Acoustics
- Signal Processing
- Speech Science
Background:
- Fundamental frequency (fo) estimation is crucial for analyzing speech and music.
- Visual analysis of spectrograms/waveforms is unreliable when the lowest harmonic is weak or subharmonics are present.
Purpose of the Study:
- To evaluate the performance of fundamental frequency extraction algorithms under challenging conditions.
- To assess algorithm accuracy when the fundamental frequency component is weak, absent, or obscured by subharmonics.
Main Methods:
- Generated composite waveforms with varying sinusoidal component amplitudes and phases.
- Employed state-of-the-art algorithms to extract fo.
- Defined fundamental frequency using the greatest common divisor (GCD) of harmonic components.
Main Results:
- Most algorithms correctly identified the GCD as fo, even with a missing fundamental and only two harmonics.
- Period-2 subharmonics were incorrectly identified as fo when their amplitude exceeded 30% of the lowest harmonic's amplitude.
Conclusions:
- Fundamental frequency extraction from complex signals requires careful consideration, especially in speech and music.
- Further research should investigate period-3/4 subharmonics, sidebands, and difference frequencies.
- Perceptual studies are needed to validate GCD predictions against human auditory perception.
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