I have a phone record with two persons speaking, let's call them A and B. A is very quiet on the record, B is "normal".

Now I want to amplify the voice of person A so that it matches the loudness of person B. How can that be done?

Note that I don't care about noise or whatever, I need no filtering, I just need to amplify the voice of person A.

Please note that it is a longer record, so I need an automatic solution, amplifying person A manually would take hours.


3 Answers 3


Use dynamic range compression.

Set the threshold to kick in only on the louder voice, and adjust the ratio until the levels between the two voices match. Attack and release times of about 100ms should work.

  • If you're willing to spend some money, WAVES has a Dynamic Range Comp specific for spoken audio - I just can't remember its name.
    – Johnny Bigoode
    Dec 27, 2011 at 16:27

You need to normalize the audio. There will be nothing you can do about the points in time when A and B are speaking simultaneously, but if there is that much difference between the two people, then normalization will do the trick. There are numerous commercial, shareware, and possibly free applications that can normalize an audio file.

One bit of advice. If there is a lot of noise in the audio file, you may want to damp it down a bit with a little EQ before normalizing so the process doesn't see the noise as the "high volume ceiling".

  • 1
    Normalization will adjust the overall level of the audio, not the relative levels of the two speakers. You could select individual phrases and normalize them independently, but the OP said "I need an automatic solution, amplifying person A manually would take hours".
    – smokris
    Nov 11, 2011 at 17:43
  • 1
    That's true. Compression/Expansion is probably the best bet in this case.
    – Zeronyne
    Nov 15, 2011 at 16:29

As another option, consider using The Levelator — a free application for Windows, Mac OS X, and Linux, intended to adjust audio levels within a recording, using a combination of compression and normalization.

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