我有200多个MP3文件,我需要使用静音检测来拆分其中的每个文件。我尝试了Audacity和WavePad,但它们没有批处理过程,将它们一一制作很慢。
场景如下:
我尝试了FFmpeg,但没有成功。
我发现pydub是用简单的方法和紧凑的代码来进行这种音频处理的最简单工具。
您可以安装pydub与
pip install pydub
如果需要,您可能需要安装ffmpeg / avlib。有关更多详细信息,请参见此链接。
这是您要执行的代码段。某些参数(例如silence_threshold
和)target_dBFS
可能需要进行调整以符合您的要求。总体而言,mp3
尽管我必须尝试为设置不同的值,但我仍然能够拆分文件silence_threshold
。
片段
# Import the AudioSegment class for processing audio and the
# split_on_silence function for separating out silent chunks.
from pydub import AudioSegment
from pydub.silence import split_on_silence
# Define a function to normalize a chunk to a target amplitude.
def match_target_amplitude(aChunk, target_dBFS):
''' Normalize given audio chunk '''
change_in_dBFS = target_dBFS - aChunk.dBFS
return aChunk.apply_gain(change_in_dBFS)
# Load your audio.
song = AudioSegment.from_mp3("your_audio.mp3")
# Split track where the silence is 2 seconds or more and get chunks using
# the imported function.
chunks = split_on_silence (
# Use the loaded audio.
song,
# Specify that a silent chunk must be at least 2 seconds or 2000 ms long.
min_silence_len = 2000,
# Consider a chunk silent if it's quieter than -16 dBFS.
# (You may want to adjust this parameter.)
silence_thresh = -16
)
# Process each chunk with your parameters
for i, chunk in enumerate(chunks):
# Create a silence chunk that's 0.5 seconds (or 500 ms) long for padding.
silence_chunk = AudioSegment.silent(duration=500)
# Add the padding chunk to beginning and end of the entire chunk.
audio_chunk = silence_chunk + chunk + silence_chunk
# Normalize the entire chunk.
normalized_chunk = match_target_amplitude(audio_chunk, -20.0)
# Export the audio chunk with new bitrate.
print("Exporting chunk{0}.mp3.".format(i))
normalized_chunk.export(
".//chunk{0}.mp3".format(i),
bitrate = "192k",
format = "mp3"
)
如果您的原始音频是立体声(2声道),则您的块也将是立体声。您可以像这样检查原始音频:
>>> song.channels
2
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