Stft

STFT for Classification

STFT for Classification
  1. What is STFT used for?
  2. How is STFT calculated?
  3. What are the advantages of STFT over a simple FFT?
  4. Why would we use a STFT spectrogram for Analysing human speech?

What is STFT used for?

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 is STFT calculated?

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 are the advantages of STFT over a simple FFT?

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.

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