What is the most accurate method for extracting formant frequencies from a speech sample?

The most accurate method for extracting formant frequencies from a speech sample is linear predictive coding (LPC). LPC is a powerful technique used in speech processing that models the vocal tract as a series of resonant filters. By analyzing the speech signal, LPC can effectively estimate the parameters that describe the formant frequencies, which are the resonant frequencies of the vocal tract.

This method is particularly effective because it reduces the complexity of the speech signal by focusing on the formants, which are critical for understanding vowel sounds and certain consonant sounds. LPC works by minimizing the difference between the actual speech signal and a model of that signal, which results in an accurate representation of the formants.

While waveform analysis provides a visual representation of the amplitude variations over time and can give insight into the speech signal, it does not specifically isolate formant frequencies. The Fourier transform can analyze the frequency content of a signal but provides a broader picture of all frequency components, rather than focusing on the resonant characteristics essential for formant extraction. Spectrographic analysis gives a visual representation of the spectrum of frequencies present in the speech signal over time, and while it helps to visualize formant frequencies, it does not provide the precision in parameter estimation that LPC does.

Thus, linear predictive