Understanding Pitch Detection with Autocorrelation Methods

1. How do you find pitch from autocorrelation?
2. What are different methods of pitch tracking?
3. How does pitch detection work?
4. What is the autocorrelation of a speech signal?

How do you find pitch from autocorrelation?

The first step is to divide the given speech signal into 30-40ms blocks of speech frames. The auto correlation sequence of each frame is then found. The pitch period can be computed by finding the time lag corresponds to the second largest peak from the central peak of autocorrelation sequence.

What are different methods of pitch tracking?

Among the various pitch detection algorithms, the following methods can be selected: modified autocorrelation method (AUTOC),² cepstrum method, multiband summary correlogram (MBSC),⁶ BaNa,⁷ YIN,⁴ yet another algorithm for pitch tracking (YAAPT),⁵ average magnitude difference function (AMDF),² SWIPE,²⁹ and pitch ...

How does pitch detection work?

Perhaps the most basic algorithm that can be considered for pitch detection is the zero crossing method. As the name implies, this technique works by analyzing an audio signal in the time domain and counting the number of times the amplitude of the wave changes from a positive to a negative value.

What is the autocorrelation of a speech signal?

"Autocorrelation" is used to compare a signal with a time-delayed version of itself. If a signal is periodic, then the signal will be perfectly correlated with a version of itself if the time-delay is an integer number of periods.