In the VA5505's audio example, when you played your own audio signal to the codec, and then transfer it into DSP to do a lowpass filtering , you will hear some unexpected noise mixed in your filtered output audio signal if you use a earphone to hear it .
The noise you hear is a result of the block processing required by the FFT. The stream of audio samples is broken into blocks, and processed as blocks, then recombined into a single stream prior to output. The Constant Overlap and Add (COLA) method used to recombine blocks, but there is a small discontinuity between blocks causing periodic noise.
Overlap-add have to do with accounting for FFT periodicity when applied to segmented or non-periodic data, for example when performing convolution or correlation in the frequency domain. In such case, perfect reconstruction of segmented data is required so overlap-add is applied to time domain data *after* inverse FFT.
Overlap *prior* to FFT, done in the time domain and used in STFT analysis (as one example), is more basic. Normally overlap is combined with a time domain window (Hamming, Hanning, Blackman, etc) to avoid "edge noise"; i.e. noise effects due to arbitarily segmenting continuous time domain data (like speech or other audio). Typically a combination like 50% overlap and Hanning window is used... this eliminates wide-band noise due to segmentation, while still allowing each time domain sample to "contribute equally" to the final STFT result (i.e. compensate for window weighting). The tradeoff is some loss in frequency domain precision. (if there are some point that is not proper, we like to discuss and improve it )
