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I am developing app to detect the inability of elderly people to unlock their rooms using IC cards in their daycare center. This room doors has an electronic circuit that emits beep sounds d to signal the user failure in unlock the room. My goal is to detect this beep signal. I have searched a lot and found some possibilities:

  1. To clip the beep sound and use as a template signal and compare it with test signal (the complete human door interaction audio clip) using convolution, matched filters, DTW or what so ever to measure their similarity. What do u recommend and how to implement it.

  2. To analyze the FFT of beep sound to see if it has a frequency band different that of the background noise. I do not understand how to do it exactly?

  3. To check whether the beep sound form a peak at certain frequency spectrum that is absent in the background noise. If so, Implement a freclipped the beep sound and got the spectrogram as shown in the figure spectrogram of beep sound. but i cannot interpret it? could u give me a detailed explanation of the spectrogram.

3.What is your recommendation? If you have other efficient method for beep detection, please explain.

Elhamshary
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1 Answers1

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There is no need to calculate the full spectrum. If you know the frequency of the beep, you can just do a single point DFT and continuously check the level at that frequency. If you detect a rising and falling edge within a given interval it must be the beep sound.

You might want to have a look at the Goertzel Algorithm. It is an algorithm for continuous single point DFT calculation.

maniacmic
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