Cut out multiple similar sound

Hello,
I have an audiobook wich have after each section an annoying monkeys sound. All is the same. All have break before and after so it is easy to detect it
But there are lot in the audiobook.
I would like to cut them out all.

What is the easiest way to cut them out?

Could you please write it to me step by step.

annoying monkeys sound.

Select ten seconds of voice recording with the noise. Both is best. Post it on the forum.

https://forum.audacityteam.org/t/how-to-post-an-audio-sample/29851/1

Even if we do come up with a way to delete the noise, it’s going to leave holes in the reading that may sound weird or unusual. You may have to patch by hand anyway.

Do you know where the noise is coming from? Has it made noise from the first chapter?

What’s the microphone and how is it connected? Are you recording on the computer? Laptop?

Koz

Hello,
This is not noise.
Those are monkeys sounds, loughing monkeys.
They separated the parts with it.
So read a part, break, monkeys sound, break, read more, break, monkeys sounds, break, read more…
Like this. So it is the part of the audiobook, but annoying.
It is not fits to the book, it is loud, so will be better without.
How can I upload that sound here?

Here is the audiobook https://youtu.be/nXvMvp7Mky4
03:00 and 07:26 you can hear the monkeys.

You’ll probably have to edit them out one-at-a-time manually. (Select/highlight and hit the Del key on your keyboard.)
Audio editing (and video editing) is time consuming… It generally takes more than an hour to edit a one-hour recording, depending on what you’re doing. “Typically”, I’d say it takes more than 3 times the playing-time… You’re usually going to listen-through before you start, then you have to listen while you edit (starting & stopping), and then you’re going to listen to the whole thing again when you’re done…


…I’m working on a project now where I’m adding time-stamps to song lyrics for synchronized lyrics. (This is with MiniLyrics, not Audacity.) I already have the lyrics so I don’t have to type them but it’s still taking me about a half-hour (maybe more) for each song! I just have to add the beginning-time for each line but I have to start & stop and check to make sure the times are right so I’m listening to the song multiple times (in bits & pieces) and I have to stop to type-in the times.

First of all thenks for your answer :slight_smile:
One by one is not a solution.
Almost every 3rd minutes have this sound, the full book is more than 40 hours.
That would be never ending editing for listening once and delete.
It have to be some solution, because it is the same sound all the time.
The app can noise filter, so if I mark this as a noise I can mute this parts, but after how can I delete those muted parts?
So I know there should have to be a solution, but how.

Noise reduction won’t work… Noise reduction looks for spectral (frequency) information, not “sound patterns”.

I don’t know if there’s any way to do it. Theoretically, it could be done with voice recognition and a program like [u]Dragon[/u] could probably be trained to find all of the laughing monkeys, but I don’t think it can automatically edit a WAV file.

I don’t know if there’s any way to do it.

I don’t think so, either. Audacity can’t be used to separate a mixed performance into individual voices, instruments, or sounds. It seems easy to you because your head recognizes that pattern of tones as a monkey laugh, but to Audacity, it’s just a bunch of tones with no clear identity. There is no “Delete Everything Annoying” tool.

There is something bothering me. I can’t believe any company would publish an audiobook composed like that. I wonder if the effects on the book are broken, or you’re listening wrong. For example, if you’re listening in mono and the voice partially cancels due to a microphone error, then the monkeys might be way louder than the narration. If you listen in stereo, the narration would be a more normal volume and the monkeys would sink to background effects or interstitials rather than obnoxiously loud.

Koz

Thank you so much for yor help /all of you/ :wink: