Short-time fourier transform spectrogram

1. What is STFT spectrogram?
2. What does short-time Fourier transform do?
3. How do you find the short-time Fourier transform?
4. What is the output of short-time Fourier transform?
5. Is STFT and FFT same?
6. Why would we use a STFT spectrogram for Analysing human speech?

What is STFT spectrogram?

s = spectrogram( x ) returns the Short-Time Fourier Transform (STFT) of the input signal x . Each column of s contains an estimate of the short-term, time-localized frequency content of x . The magnitude squared of s is known as the spectrogram time-frequency representation of x [1].

What does short-time Fourier transform do?

The short-time Fourier transform (STFT) is used to analyze how the frequency content of a nonstationary signal changes over time. The magnitude squared of the STFT is known as the spectrogram time-frequency representation of the signal.

How do you find the short-time Fourier transform?

In practice, the procedure for computing STFTs is to divide a longer time signal into shorter segments of equal length and then compute the Fourier transform separately on each shorter segment. This reveals the Fourier spectrum on each shorter segment.

What is the output of short-time Fourier transform?

7.2 Short-Time Fourier Transform (STFT)

STFT provides the time-localized frequency information for situations in which frequency components of a signal vary over time, whereas the standard Fourier transform provides the frequency information averaged over the entire signal time interval.

Is STFT and FFT same?

If you look closely, there is a difference in the time frame on 3D graphs between STFT and FFT. STFT has smaller time frames, consequently, the frequency spectrum moves smoother over time, therefore it is more accurate. Block size - defines the number of real data samples to be taken for the calculating FFT.

Why would we use a STFT spectrogram for Analysing human speech?

The STFT is one of the most frequently used tools in speech analysis and processing. It describes the evolution of frequency components over time. Like the spectrum itself, one of the benefits of STFTs is that its parameters have a physical and intuitive interpretation.