Spectrogram Time Resolution with Overlap

1. What is time resolution for a spectrogram?
2. How do you find the resolution of a spectrogram?
3. Why do we use overlap in FFT?
4. What is FFT overlap?

What is time resolution for a spectrogram?

The temporal resolution of a spectrogram depends on hop size. Previous works generally assume the hop size should be a constant value such as ten milliseconds. However, a fixed hop size or resolution is not always optimal for different types of sound.

How do you find the resolution of a spectrogram?

Resolution The frequency resolution depends on the FFT length and the sampling frequency of the sound file. In contrast to the bandwidth, the frequency resolution corresponds to the height of one pixel of the spectrogram (frequency bin width = sample rate / FFT length).

Why do we use overlap in FFT?

FFT processing can be particularly problematic when the signal consists of randomly occurring transients superimposed on a more continuous signal. Overlap processing is commonly used in this situation to improve the estimates.

What is FFT overlap?

FFT convolution uses the overlap-add method together with the Fast Fourier Transform, allowing signals to be convolved by multiplying their frequency spectra. For filter kernels longer than about 64 points, FFT convolution is faster than standard convolution, while producing exactly the same result.