In this tutorial, we will introduce how to use python librosa to remove silence in a wav file, which is very useful if you plan to process wav files.
Here are two kinds of removing silence from wav file, we will introduce one by one.
Read a wav file using librosa
We can use librosa.load() to read a wav data. Here is an example:
import librosa import soundfile as sf audio_file = r'F:\test.wav' #read wav data audio, sr = librosa.load(audio_file, sr= 8000, mono=True) print(audio.shape, sr)
Run this code we will find:
(101600,) 8000
We can find this wav file contains 101600 length data.
Remove silence at the beginning and end in a wav file
We can use librosa.effects.trim() to do it.
librosa.effects.trim() is defined as:
def trim(y, top_db=60, ref=np.max, frame_length=2048, hop_length=512):
It will trim leading and trailing silence from an audio signal.
Here is an example:
clip = librosa.effects.trim(audio, top_db= 10) print(clip[0].shape)
In this code, we will remove audio signal that is lower than 10db.
Here clip contains audio signal without silence. We can save it as follows:
sf.write('F:\\2.wav', clip[0], sr)
Remove all silence in a wav file
We can use librosa.effects.split() to remove all silence in a wav file.
First, we can use librosa.effects.split() to split a wav file based on silence.
clips = librosa.effects.split(audio, top_db=10) print(clips)
Then, we can combine these audio clips.
wav_data = []
for c in clips:
print(c)
data = audio[c[0]: c[1]]
wav_data.extend(data)
sf.write('5s.wav', wav_data, sr)
Here top_db is important, which determines what signal is silence.
librosa.effects.split() is defined:
def split(y, top_db=60, ref=np.max, frame_length=2048, hop_length=512):
Here y is the audio data.
Moreover, if you do not want to use librosa to remove silence, you also can use VAD to remove. This way is more customizable.
Here is the tutorial:
Auido VAD: Remove Silence in WAV Using Python – Python Tutorial