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Is it possible to filter speech frequencies in a video with significant accuracy to identify the passages were people talk?

Telephony started with very bad microphones, transmitting barely anything outside the range 300 Hz to 3 kHz, but that was "good enough". Technical development improved the microphones, but analog telephony was and still is intentionally limited to that frequency range. Even when switching to ISDN, the sampling rate was only 8 kHz, limiting audio to about 3 kHz. Things changed only after migration to SIP, with "HD" audio codecs that allow higher frequencies, using more bandwidth and/or more available computing power.

So I would expect that a filter with that frequency range could be a usable indicator for speech.

Unfortunately, because the human ear is most sensitive in exactly this range, almost all audible warning signals also use that frequency range. So you will get some false positives. A FFT should be able to identify sharp peaks coming from all kind of beepers and ignore those peaks.


Today I will gladly share my knowledge and experience, for there are no sweeter words than "I told you so". ;-)

In reply to Re: Adjust synchronizations of video and subtitles automatically by temporal distribution by afoken
in thread Adjust synchronizations of video and subtitles automatically by temporal distribution by LanX

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