Update tech_docs/music/guide_to_working_with_audio_on_linux.md
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### Comprehensive Guide to Working with Audio Tracks on Linux
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This guide will provide you with the necessary tools and steps to convert MP3 files to WAV, separate audio tracks, and analyze and manipulate these tracks using a combination of tools such as FFmpeg, yt-dlp, Spleeter, Audacity, Librosa, and PyDub.
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#### Tools You Will Use
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1. **FFmpeg**: For converting audio files between formats.
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2. **yt-dlp**: For downloading audio from YouTube.
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3. **Spleeter**: For separating audio tracks into stems (vocals, instruments).
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4. **Audacity**: For manual audio editing.
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5. **Librosa**: For detailed audio analysis.
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6. **PyDub**: For automated audio manipulation.
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### Step-by-Step Process
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#### 1. Downloading Audio from YouTube
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**Tool**: `yt-dlp`
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**Installation**:
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```bash
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pip install yt-dlp
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sudo apt install ffmpeg # Required for audio extraction
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```
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**Usage**:
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- Download and convert YouTube video to MP3:
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```bash
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yt-dlp -x --audio-format mp3 <YouTube-URL>
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```
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#### 2. Converting MP3 to WAV
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**Tool**: `FFmpeg`
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**Installation**:
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```bash
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sudo apt install ffmpeg
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```
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**Usage**:
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- Convert MP3 to WAV:
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```bash
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ffmpeg -i input.mp3 output.wav
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```
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#### 3. Separating Audio Tracks
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**Tool**: `Spleeter`
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**Installation**:
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```bash
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pip install spleeter
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```
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**Usage**:
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- Separate into 2 stems (vocals and accompaniment):
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```bash
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spleeter separate -i output.wav -p spleeter:2stems -o output/
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```
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#### 4. Manual Audio Editing
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**Tool**: `Audacity`
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**Installation**:
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```bash
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sudo apt install audacity
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```
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**Usage**:
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1. Open Audacity and import the WAV files:
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- `File > Import > Audio...`
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2. Use the editing tools to apply effects, trim, and adjust tracks.
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3. Export the edited tracks:
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- `File > Export > Export as WAV...`
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#### 5. Detailed Audio Analysis
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**Tool**: `Librosa`
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**Installation**:
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```bash
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pip install librosa matplotlib numpy scipy
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```
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**Usage**:
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- Analyze and visualize audio features:
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```python
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import librosa
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import matplotlib.pyplot as plt
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y, sr = librosa.load('output/vocals.wav', sr=None)
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plt.figure(figsize=(14, 5))
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librosa.display.waveshow(y, sr=sr)
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plt.title('Waveform')
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plt.show()
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D = np.abs(librosa.stft(y))
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DB = librosa.amplitude_to_db(D, ref=np.max)
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plt.figure(figsize=(14, 5))
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librosa.display.specshow(DB, sr=sr, x_axis='time', y_axis='log')
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plt.colorbar(format='%+2.0f dB')
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plt.title('Spectrogram')
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plt.show()
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```
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#### 6. Automated Audio Manipulation
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**Tool**: `PyDub`
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**Installation**:
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```bash
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pip install pydub
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```
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**Usage**:
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- Load and manipulate audio:
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```python
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from pydub import AudioSegment
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sound = AudioSegment.from_wav('output/vocals.wav')
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louder_sound = sound + 6 # Increase volume by 6 dB
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louder_sound.export('output/louder_vocals.wav', format='wav')
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```
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### Project Structure and Best Practices
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1. **Organize Your Files**:
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- Create a project directory with subdirectories for raw files, separated stems, edited files, and final outputs.
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```
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project_directory/
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├── raw_files/
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│ ├── input.mp3
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├── separated_stems/
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│ ├── vocals.wav
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│ ├── accompaniment.wav
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├── edited_files/
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│ ├── edited_vocals.wav
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├── final_outputs/
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│ ├── final_output.mp3
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```
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2. **Use Scripts for Automation**:
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- Create scripts to automate repetitive tasks like downloading, converting, and processing audio files.
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- Example script for downloading and converting:
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```bash
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#!/bin/bash
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yt-dlp -x --audio-format mp3 -o 'raw_files/%(title)s.%(ext)s' $1
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ffmpeg -i raw_files/*.mp3 raw_files/*.wav
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```
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3. **Document Your Process**:
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- Keep a README file in your project directory to document the steps you’ve taken, tools used, and any important notes.
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4. **Backup Your Data**:
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- Regularly backup your project directory to prevent data loss.
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### Example Workflow
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1. **Download and Convert Audio**:
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```bash
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yt-dlp -x --audio-format mp3 -o 'raw_files/%(title)s.%(ext)s' https://www.youtube.com/watch?v=dQw4w9WgXcQ
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ffmpeg -i raw_files/*.mp3 raw_files/*.wav
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```
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2. **Separate Audio Tracks**:
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```bash
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spleeter separate -i raw_files/input.wav -p spleeter:2stems -o separated_stems/
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```
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3. **Edit Tracks in Audacity**:
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- Import `separated_stems/vocals.wav` and make adjustments.
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- Export edited file to `edited_files/edited_vocals.wav`.
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4. **Analyze and Manipulate with Python**:
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```python
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import librosa
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y, sr = librosa.load('edited_files/edited_vocals.wav', sr=None)
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# Perform analysis and visualization
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from pydub import AudioSegment
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sound = AudioSegment.from_wav('edited_files/edited_vocals.wav')
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louder_sound = sound + 6
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louder_sound.export('final_outputs/final_output.wav', format='wav')
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```
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By following this guide, you can effectively manage and process audio tracks using a combination of powerful tools available on Linux.
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### Analyze Programmatically Using Librosa for Detailed Feature Extraction and PyDub for Automated Audio Manipulations
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#### Librosa: Detailed Feature Extraction
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