Audio Editing Automation
FFmpeg Audio Operations
Extract Audio from Video
ffmpeg -i input.mp4 -vn -acodec copy audio.aac
# -vn: no video
# -acodec copy: no re-encoding
Audio Format Conversion
# WAV to MP3
ffmpeg -i input.wav -c:a libmp3lame -b:a 192k output.mp3
# MP3 to AAC
ffmpeg -i input.mp3 -c:a aac -b:a 192k output.m4a
Volume Normalization
# Increase volume by 10dB
ffmpeg -i input.mp3 -af "volume=10dB" output.mp3
# Normalize using loudnorm filter
ffmpeg -i input.wav -af "loudnorm=I=-16:TP=-1.5:LRA=11" output.wav
Audio Mixing
# Mix two audio files
ffmpeg -i voice.mp3 -i music.mp3 -filter_complex amix=inputs=2:duration=longest output.mp3
# Voice + background music (ducking)
ffmpeg -i voice.mp3 -i music.mp3 -filter_complex \
"[1:a]volume=0.3[bg];[0:a][bg]amix=inputs=2:duration=first" output.mp3
Batch Processing
import subprocess
from pathlib import Path
def normalize_audio_batch(input_dir, output_dir):
for audio in Path(input_dir).glob("*.mp3"):
output = Path(output_dir) / audio.name
subprocess.run([
'ffmpeg', '-i', str(audio),
'-af', 'loudnorm=I=-16:TP=-1.5',
str(output)
])
Audio Quality Standards
Podcast Export
Format: MP3
Bitrate: 128-192kbps
Sample Rate: 44.1kHz
Loudness: -16 LUFS
Peak: -1dB
Audiobook (ACX)
Format: MP3, 192kbps CBR
Sample Rate: 44.1kHz
Peak: -3dB
RMS: -18dB to -23dB
Noise Floor: -60dB
YouTube/Video
Format: AAC
Bitrate: 192kbps
Sample Rate: 48kHz
Loudness: -14 LUFS
Automation Workflow
def audio_production_pipeline(voice_file, music_file):
# 1. Normalize voice
normalize_audio(voice_file, 'voice_normalized.mp3')
# 2. Mix with music
mix_audio('voice_normalized.mp3', music_file, 'mixed.mp3')
# 3. Final loudness normalization
final_normalize('mixed.mp3', 'final.mp3', target_lufs=-16)
# 4. Export for platforms
export_for_podcast('final.mp3')
export_for_youtube('final.mp3')
Resources
- FFmpeg Audio Documentation
- Loudness Standards (LUFS)
- Audio Mastering Best Practices
majiayu000