Incremental Audio Workflow

Incremental Audio Production Workflow

This skill provides a resilient pattern for audio production that emphasizes incremental verification and fail-fast principles. Each major step produces verified outputs before proceeding, reducing iteration count and catching errors early.

Overview

Follow these steps in strict order. Each step must complete successfully and pass verification before proceeding to the next:

1. Early timing calculation - Derive section transitions from BPM and duration first
2. Verify reference audio - Validate input file properties
3. Generate and verify each stem individually - One stem at a time with immediate verification
4. Generate drum stem separately - Dedicated drum extension with rhythm patterns
5. Apply effects with verification - Process each stem and verify output
6. Export master track - Mix all verified stems
7. Archive and final verification - Package deliverables with comprehensive checks

Key Differences from Standard Workflow

• Incremental verification: Verify each stem immediately after generation, not just at the end
• Fail-fast approach: Stop and report errors at each step rather than accumulating failures
• Early timing: Calculate section transitions before any audio generation
• Separated drums: Drum stem generation is a distinct step with rhythm-specific processing
• Memory-efficient: Process stems individually to avoid large array operations that cause sandbox failures

Step 1: Calculate Timing Parameters (Early)

Calculate all timing parameters before generating any audio. This ensures consistent timing across all stems:

pythonCopy code
def calculate_section_transitions(bpm, total_duration_sec, sections):
    """Calculate beat-aligned transition points for song sections."""
    beats_per_second = bpm / 60.0
    
    section_durations = {}
    cumulative_time = 0
    
    for section_name, beat_count in sections.items():
        duration = beat_count / beats_per_second
        section_durations[section_name] = {
            'start': cumulative_time,
            'end': cumulative_time + duration,
            'beats': beat_count,
            'start_beat': cumulative_time * beats_per_second
        }
        cumulative_time += duration
    
    return section_durations

# Configuration
BPM = 120
DURATION = 137
SECTIONS = {'intro': 16, 'verse': 32, 'chorus': 32, 'bridge': 16, 'outro': 16}

timing = calculate_section_transitions(BPM, DURATION, SECTIONS)
print("Timing calculated:")
for section, data in timing.items():
    print(f"  {section}: {data['start']:.2f}s - {data['end']:.2f}s ({data['beats']} beats)")

Step 2: Verify Reference Audio

Validate the reference file exists and has expected properties:

pythonCopy code
import soundfile as sf
import os

def verify_reference_file(filepath, expected_sample_rate=None, min_duration=None):
    """Verify reference audio file and return info dict."""
    if not os.path.exists(filepath):
        raise FileNotFoundError(f"Reference file not found: {filepath}")
    
    info = sf.info(filepath)
    errors = []
    
    if expected_sample_rate and info.samplerate != expected_sample_rate:
        errors.append(f"Sample rate mismatch: expected {expected_sample_rate}, got {info.samplerate}")
    
    if min_duration and info.duration < min_duration:
        errors.append(f"Duration too short: expected >= {min_duration}s, got {info.duration}s")
    
    if errors:
        raise ValueError(f"Reference file validation failed: {'; '.join(errors)}")
    
    print(f"Reference verified: {info.duration:.2f}s @ {info.samplerate}Hz, {info.channels}ch, {info.subtype}")
    return {
        'sample_rate': info.samplerate,
        'duration': info.duration,
        'channels': info.channels,
        'subtype': info.subtype
    }

# Verify reference
ref_info = verify_reference_file('reference.wav', expected_sample_rate=48000, min_duration=130)

Step 3: Generate and Verify Each Stem Individually

Generate one stem at a time, verify it immediately before proceeding to the next:

pythonCopy code
import numpy as np

def generate_stem(name, duration_sec, sample_rate, subtype='FLOAT', section_timing=None):
    """Generate a single stem with explicit sample type."""
    frames = int(duration_sec * sample_rate)
    t = np.linspace(0, duration_sec, frames)
    
    # Generate stem-specific content (customize per stem type)
    if name == 'bass':
        freq = 110  # A2
        audio_data = np.sin(2 * np.pi * freq * t) * 0.8
    elif name == 'guitars':
        freq = 440  # A4
        audio_data = np.sin(2 * np.pi * freq * t) * 0.6
    elif name == 'synths':
        freq = 880  # A5
        audio_data = np.sin(2 * np.pi * freq * t) * 0.5
    elif name == 'bridge':
        freq = 220  # A3
        audio_data = np.sin(2 * np.pi * freq * t) * 0.7
    else:
        audio_data = np.sin(2 * np.pi * 440 * t) * 0.5
    
    # Ensure proper data type
    if subtype == 'FLOAT':
        audio_data = audio_data.astype(np.float32)
    elif subtype == 'PCM_24':
        audio_data = np.clip(audio_data, -1, 1) * (2**23 - 1)
        audio_data = audio_data.astype(np.int32)
    
    filepath = f'{name}_stem.wav'
    sf.write(filepath, audio_data, sample_rate, subtype=subtype, format='WAV')
    
    return filepath, audio_data

def verify_stem(filepath, expected_sample_rate, expected_subtype, expected_duration):
    """Verify a single stem meets specifications."""
    if not os.path.exists(filepath):
        return {'success': False, 'error': f'File not found: {filepath}'}
    
    info = sf.info(filepath)
    errors = []
    
    if info.samplerate != expected_sample_rate:
        errors.append(f'sample_rate: expected {expected_sample_rate}, got {info.samplerate}')
    
    if info.subtype != expected_subtype:
        errors.append(f'subtype: expected {expected_subtype}, got {info.subtype}')
    
    if abs(info.duration - expected_duration) > 1.0:  # Allow 1s tolerance
        errors.append(f'duration: expected ~{expected_duration}s, got {info.duration}s')
    
    if errors:
        return {'success': False, 'error': '; '.join(errors)}
    
    return {'success': True, 'info': info}

# Generate stems one at a time with verification
SAMPLE_RATE = 48000
SUBTYPE = 'FLOAT'
STEM_NAMES = ['bass', 'guitars', 'synths', 'bridge']

generated_stems = []
for stem_name in STEM_NAMES:
    print(f"\n=== Generating {stem_name} stem ===")
    
    # Generate
    filepath, data = generate_stem(stem_name, DURATION, SAMPLE_RATE, subtype=SUBTYPE)
    
    # Verify immediately
    result = verify_stem(filepath, SAMPLE_RATE, SUBTYPE, DURATION)
    
    if result['success']:
        print(f"✓ {stem_name} stem verified: {result['info'].duration:.2f}s @ {result['info'].samplerate}Hz")
        generated_stems.append(filepath)
    else:
        print(f"✗ {stem_name} stem FAILED: {result['error']}")
        raise RuntimeError(f"Stem generation failed for {stem_name}: {result['error']}")

print(f"\nAll {len(generated_stems)} stems generated and verified successfully")

Step 4: Generate Drum Stem Separately

Drums require different processing (rhythm patterns, percussion sounds):

pythonCopy code
def generate_drum_stem(duration_sec, sample_rate, bpm, section_timing, subtype='FLOAT'):
    """Generate drum stem with rhythm patterns aligned to sections."""
    frames = int(duration_sec * sample_rate)
    audio_data = np.zeros(frames, dtype=np.float32)
    beats_per_second = bpm / 60.0
    
    # Simple kick drum pattern (every beat)
    kick_freq = 60
    kick_duration = 0.1
    kick_frames = int(kick_duration * sample_rate)
    
    for beat_time in np.arange(0, duration_sec, 1.0 / beats_per_second):
        start_frame = int(beat_time * sample_rate)
        end_frame = min(start_frame + kick_frames, frames)
        
        if start_frame < frames:
            t = np.linspace(0, kick_duration, end_frame - start_frame)
            kick = np.exp(-5 * t) * np.sin(2 * np.pi * kick_freq * t)
            audio_data[start_frame:end_frame] += kick * 0.9
    
    # Simple snare pattern (every 2nd and 4th beat)
    snare_freq = 200
    snare_duration = 0.05
    snare_frames = int(snare_duration * sample_rate)
    
    for beat_time in np.arange(0, duration_sec, 2.0 / beats_per_second):
        start_frame = int((beat_time + 0.5 / beats_per_second) * sample_rate)
        end_frame = min(start_frame + snare_frames, frames)
        
        if start_frame < frames:
            t = np.linspace(0, snare_duration, end_frame - start_frame)
            snare = np.exp(-10 * t) * np.random.uniform(-1, 1, len(t)) * 0.5
            audio_data[start_frame:end_frame] += snare * 0.7
    
    audio_data = np.clip(audio_data, -1, 1)
    
    filepath = 'drums_stem.wav'
    sf.write(filepath, audio_data, sample_rate, subtype=subtype, format='WAV')
    
    return filepath, audio_data

print("\n=== Generating drum stem ===")
drums_filepath, drums_data = generate_drum_stem(DURATION, SAMPLE_RATE, BPM, timing, subtype=SUBTYPE)

drums_result = verify_stem(drums_filepath, SAMPLE_RATE, SUBTYPE, DURATION)
if drums_result['success']:
    print(f"✓ Drum stem verified: {drums_result['info'].duration:.2f}s @ {drums_result['info'].samplerate}Hz")
    generated_stems.append(drums_filepath)
else:
    print(f"✗ Drum stem FAILED: {drums_result['error']}")
    raise RuntimeError(f"Drum stem generation failed: {drums_result['error']}")

Step 5: Apply Effects with Verification

Process each stem and verify the output:

pythonCopy code
from scipy import signal

def apply_lowpass_filter(audio_data, sample_rate, cutoff_freq=8000):
    """Apply lowpass filter using scipy.signal."""
    nyquist = sample_rate / 2
    normalized_cutoff = cutoff_freq / nyquist
    b, a = signal.butter(4, normalized_cutoff, btype='low')
    return signal.filtfilt(b, a, audio_data)

def apply_effects_and_verify(input_filepath, output_filepath, sample_rate, subtype):
    """Apply effects to stem and verify output."""
    data, sr = sf.read(input_filepath)
    
    # Apply effects
    processed = apply_lowpass_filter(data, sr, cutoff_freq=8000)
    processed = np.clip(processed, -1, 1)
    
    # Export
    sf.write(output_filepath, processed, sample_rate, subtype=subtype, format='WAV')
    
    # Verify
    result = verify_stem(output_filepath, sample_rate, subtype, DURATION)
    return result, processed

print("\n=== Applying effects to all stems ===")
processed_stems = []

for stem_name in STEM_NAMES:
    input_file = f'{stem_name}_stem.wav'
    output_file = f'{stem_name}_processed.wav'
    
    print(f"Processing {stem_name}...")
    result, _ = apply_effects_and_verify(input_file, output_file, SAMPLE_RATE, SUBTYPE)
    
    if result['success']:
        print(f"✓ {stem_name} processed and verified")
        processed_stems.append(output_file)
    else:
        print(f"✗ {stem_name} processing FAILED: {result['error']}")
        raise RuntimeError(f"Effects processing failed for {stem_name}")

# Process drums separately
drums_output = 'drums_processed.wav'
drums_result, _ = apply_effects_and_verify('drums_stem.wav', drums_output, SAMPLE_RATE, SUBTYPE)
if drums_result['success']:
    print(f"✓ Drums processed and verified")
    processed_stems.append(drums_output)
else:
    raise RuntimeError(f"Drums processing failed: {drums_result['error']}")

Step 6: Export Master Track

Mix all verified stems into master track:

pythonCopy code
def create_master_track(stem_files, output_filepath, sample_rate, subtype):
    """Create master track from verified stems."""
    # Load first stem to get dimensions
    first_data, sr = sf.read(stem_files[0])
    master_audio = np.zeros(len(first_data), dtype=np.float32)
    
    # Mix all stems with gain staging
    gain_per_stem = 0.4  # Prevent clipping with 5 stems
    
    for stem_file in stem_files:
        data, _ = sf.read(stem_file)
        if len(data) == len(master_audio):
            master_audio += data * gain_per_stem
        else:
            print(f"WARNING: {stem_file} has different length, skipping")
    
    # Final limiting
    master_audio = np.clip(master_audio, -1, 1)
    
    # Export
    sf.write(output_filepath, master_audio, sample_rate, subtype=subtype, format='WAV')
    
    # Verify
    info = sf.info(output_filepath)
    return {'success': True, 'info': info}

print("\n=== Creating master track ===")
master_result = create_master_track(processed_stems, 'master_track.wav', SAMPLE_RATE, SUBTYPE)

if master_result['success']:
    print(f"✓ Master track created: {master_result['info'].duration:.2f}s @ {master_result['info'].samplerate}Hz")
else:
    raise RuntimeError("Master track creation failed")

Step 7: Archive and Final Verification

Package all deliverables and perform comprehensive verification:

pythonCopy code
import zipfile

def create_archive(archive_name, file_list):
    """Create zip archive and verify contents."""
    with zipfile.ZipFile(archive_name, 'w', zipfile.ZIP_DEFLATED) as zipf:
        for filepath in file_list:
            if os.path.exists(filepath):
                zipf.write(filepath, os.path.basename(filepath))
            else:
                raise FileNotFoundError(f"Cannot archive: {filepath} not found")
    
    # Verify archive
    with zipfile.ZipFile(archive_name, 'r') as zipf:
        contents = zipf.namelist()
    
    return {'success': True, 'file_count': len(contents), 'files': contents}

def final_verification(specs):
    """Comprehensive final verification of all outputs."""
    results = {'passed': 0, 'failed': 0, 'details': []}
    
    for filepath, expected in specs.items():
        if not os.path.exists(filepath):
            results['failed'] += 1
            results['details'].append(f"MISSING: {filepath}")
            continue
        
        info = sf.info(filepath)
        errors = []
        
        if expected.get('sample_rate') and info.samplerate != expected['sample_rate']:
            errors.append(f"sample_rate: {info.samplerate} != {expected['sample_rate']}")
        
        if expected.get('subtype') and info.subtype != expected['subtype']:
            errors.append(f"subtype: {info.subtype} != {expected['subtype']}")
        
        if expected.get('min_duration') and info.duration < expected['min_duration']:
            errors.append(f"duration: {info.duration}s < {expected['min_duration']}s")
        
        if errors:
            results['failed'] += 1
            results['details'].append(f"FAILED: {filepath} - {'; '.join(errors)}")
        else:
            results['passed'] += 1
            results['details'].append(f"PASSED: {filepath} ({info.duration:.2f}s, {info.samplerate}Hz)")
    
    return results

print("\n=== Creating archive ===")
deliverables = ['master_track.wav'] + STEM_NAMES + ['drums']
deliverable_files = [f'{name}.wav' if name != 'drums' else 'drums_processed.wav' for name in ['master_track'] + STEM_NAMES + ['drums_processed']]
deliverable_files = ['master_track.wav'] + [f'{s}_processed.wav' for s in STEM_NAMES] + ['drums_processed.wav']

archive_result = create_archive('audio_deliverables.zip', deliverable_files)
print(f"✓ Archive created with {archive_result['file_count']} files")

print("\n=== Final verification ===")
expected_specs = {
    'master_track.wav': {'sample_rate': SAMPLE_RATE, 'subtype': SUBTYPE, 'min_duration': DURATION - 5},
}
for stem in STEM_NAMES:
    expected_specs[f'{stem}_processed.wav'] = {'sample_rate': SAMPLE_RATE, 'subtype': SUBTYPE, 'min_duration': DURATION - 5}
expected_specs['drums_processed.wav'] = {'sample_rate': SAMPLE_RATE, 'subtype': SUBTYPE, 'min_duration': DURATION - 5}

verification = final_verification(expected_specs)
print(f"\nFinal verification: {verification['passed']} passed, {verification['failed']} failed")
for detail in verification['details']:
    print(f"  {detail}")

assert verification['failed'] == 0, f"Final verification failed: {verification['details']}"
print("\n✓ Workflow completed successfully!")

Complete Workflow Script

pythonCopy code
#!/usr/bin/env python3
"""
Incremental Audio Production Workflow
Generates, verifies, and archives audio stems with fail-fast checkpoints.
"""

import soundfile as sf
import numpy as np
from scipy import signal
import zipfile
import os
import sys

# Configuration
SAMPLE_RATE = 48000
DURATION = 137
BPM = 120
SUBTYPE = 'FLOAT'
STEM_NAMES = ['bass', 'guitars', 'synths', 'bridge']
SECTIONS = {'intro': 16, 'verse': 32, 'chorus': 32, 'bridge': 16, 'outro': 16}

def calculate_section_transitions(bpm, total_duration_sec, sections):
    beats_per_second = bpm / 60.0
    section_durations = {}
    cumulative_time = 0
    for section_name, beat_count in sections.items():
        duration = beat_count / beats_per_second
        section_durations[section_name] = {
            'start': cumulative_time,
            'end': cumulative_time + duration,
            'beats': beat_count
        }
        cumulative_time += duration
    return section_durations

def verify_stem(filepath, expected_sample_rate, expected_subtype, expected_duration):
    if not os.path.exists(filepath):
        return {'success': False, 'error': f'File not found: {filepath}'}
    info = sf.info(filepath)
    errors = []
    if info.samplerate != expected_sample_rate:
        errors.append(f'sample_rate mismatch')
    if info.subtype != expected_subtype:
        errors.append(f'subtype mismatch')
    if abs(info.duration - expected_duration) > 1.0:
        errors.append(f'duration mismatch')
    if errors:
        return {'success': False, 'error': '; '.join(errors)}
    return {'success': True, 'info': info}

def generate_stem(name, duration_sec, sample_rate, subtype='FLOAT'):
    frames = int(duration_sec * sample_rate)
    t = np.linspace(0, duration_sec, frames)
    freqs = {'bass': 110, 'guitars': 440, 'synths': 880, 'bridge': 220}
    freq = freqs.get(name, 440)
    audio_data = (np.sin(2 * np.pi * freq * t) * 0.5).astype(np.float32)
    filepath = f'{name}_stem.wav'
    sf.write(filepath, audio_data, sample_rate, subtype=subtype, format='WAV')
    return filepath, audio_data

def generate_drum_stem(duration_sec, sample_rate, bpm, subtype='FLOAT'):
    frames = int(duration_sec * sample_rate)
    audio_data = np.zeros(frames, dtype=np.float32)
    beats_per_second = bpm / 60.0
    for beat_time in np.arange(0, duration_sec, 1.0 / beats_per_second):
        start_frame = int(beat_time * sample_rate)
        if start_frame < frames:
            kick_duration = 0.1
            kick_frames = int(kick_duration * sample_rate)
            end_frame = min(start_frame + kick_frames, frames)
            t = np.linspace(0, kick_duration, end_frame - start_frame)
            kick = np.exp(-5 * t) * np.sin(2 * np.pi * 60 * t)
            audio_data[start_frame:end_frame] += kick * 0.9
    audio_data = np.clip(audio_data, -1, 1)
    filepath = 'drums_stem.wav'
    sf.write(filepath, audio_data, sample_rate, subtype=subtype, format='WAV')
    return filepath, audio_data

def apply_effects(input_filepath, output_filepath, sample_rate, subtype):
    data, sr = sf.read(input_filepath)
    nyquist = sample_rate / 2
    b, a = signal.butter(4, 8000 / nyquist, btype='low')
    processed = signal.filtfilt(b, a, data)
    processed = np.clip(processed, -1, 1)
    sf.write(output_filepath, processed, sample_rate, subtype=subtype, format='WAV')
    return verify_stem(output_filepath, sample_rate, subtype, DURATION)

def run_workflow():
    print("=" * 60)
    print("INCREMENTAL AUDIO PRODUCTION WORKFLOW")
    print("=" * 60)
    
    # Step 1: Calculate timing
    print("\n[Step 1] Calculating timing parameters...")
    timing = calculate_section_transitions(BPM, DURATION, SECTIONS)
    print(f"✓ Timing calculated for {len(SECTIONS)} sections")
    
    # Step 2: Verify reference
    print("\n[Step 2] Verifying reference file...")
    if os.path.exists('reference.wav'):
        ref_info = sf.info('reference.wav')
        print(f"✓ Reference: {ref_info.duration:.2f}s @ {ref_info.samplerate}Hz")
    else:
        print("! No reference file found, proceeding with defaults")
    
    # Step 3: Generate stems individually
    print("\n[Step 3] Generating stems (one at a time)...")
    generated_stems = []
    for stem_name in STEM_NAMES:
        print(f"  Generating {stem_name}...")
        filepath, _ = generate_stem(stem_name, DURATION, SAMPLE_RATE, subtype=SUBTYPE)
        result = verify_stem(filepath, SAMPLE_RATE, SUBTYPE, DURATION)
        if result['success']:
            print(f"  ✓ {stem_name} verified")
            generated_stems.append(filepath)
        else:
            print(f"  ✗ {stem_name} FAILED: {result['error']}")
            sys.exit(1)
    
    # Step 4: Generate drums
    print("\n[Step 4] Generating drum stem...")
    drums_filepath, _ = generate_drum_stem(DURATION, SAMPLE_RATE, BPM, subtype=SUBTYPE)
    drums_result = verify_stem(drums_filepath, SAMPLE_RATE, SUBTYPE, DURATION)
    if drums_result['success']:
        print(f"✓ Drums verified")
        generated_stems.append(drums_filepath)
    else:
        print(f"✗ Drums FAILED: {drums_result['error']}")
        sys.exit(1)
    
    # Step 5: Apply effects
    print("\n[Step 5] Applying effects...")
    processed_stems = []
    for stem_name in STEM_NAMES:
        input_file = f'{stem_name}_stem.wav'
        output_file = f'{stem_name}_processed.wav'
        result = apply_effects(input_file, output_file, SAMPLE_RATE, SUBTYPE)
        if result['success']:
            print(f"  ✓ {stem_name} processed")
            processed_stems.append(output_file)
        else:
            print(f"  ✗ {stem_name} processing FAILED")
            sys.exit(1)
    
    drums_processed = 'drums_processed.wav'
    drums_fx_result = apply_effects('drums_stem.wav', drums_processed, SAMPLE_RATE, SUBTYPE)
    if drums_fx_result['success']:
        print(f"  ✓ Drums processed")
        processed_stems.append(drums_processed)
    else:
        sys.exit(1)
    
    # Step 6: Create master
    print("\n[Step 6] Creating master track...")
    first_data, _ = sf.read(processed_stems[0])
    master_audio = np.zeros(len(first_data), dtype=np.float32)
    for stem_file in processed_stems:
        data, _ = sf.read(stem_file)
        master_audio += data * 0.4
    master_audio = np.clip(master_audio, -1, 1)
    sf.write('master_track.wav', master_audio, SAMPLE_RATE, subtype=SUBTYPE, format='WAV')
    master_info = sf.info('master_track.wav')
    print(f"✓ Master track: {master_info.duration:.2f}s @ {master_info.samplerate}Hz")
    
    # Step 7: Archive and verify
    print("\n[Step 7] Creating archive and final verification...")
    all_files = ['master_track.wav'] + processed_stems
    with zipfile.ZipFile('audio_deliverables.zip', 'w', zipfile.ZIP_DEFLATED) as zf:
        for f in all_files:
            zf.write(f)
    
    with zipfile.ZipFile('audio_deliverables.zip', 'r') as zf:
        print(f"✓ Archive contains {len(zf.namelist())} files")
    
    # Final verification
    specs = {f: {'sample_rate': SAMPLE_RATE, 'subtype': SUBTYPE} for f in all_files}
    passed = failed = 0
    for filepath, expected in specs.items():
        info = sf.info(filepath)
        if info.samplerate == expected['sample_rate'] and info.subtype == expected['subtype']:
            passed += 1
        else:
            failed += 1
            print(f"  ✗ {filepath} verification failed")
    
    print(f"\nFinal verification: {passed} passed, {failed} failed")
    if failed > 0:
        sys.exit(1)
    
    print("\n" + "=" * 60)
    print("WORKFLOW COMPLETED SUCCESSFULLY")
    print("=" * 60)
    return 0

if __name__ == '__main__':
    sys.exit(run_workflow())

Troubleshooting

Common Issues

Memory errors during stem generation:

• Process stems one at a time (this skill's default approach)
• Reduce duration or sample rate for testing
• Use np.float32 instead of np.float64

Sample rate mismatches:

• Always specify sample_rate explicitly in sf.write()
• Verify with sf.info() after each write operation
• Check that subtype parameter is specified

Archive creation failures:

• Verify all files exist before archiving
• Use zipfile.ZIP_DEFLATED for compression
• Check file permissions

Best Practices

1. Run incrementally: Test each step independently before running full workflow
2. Verify early: Check output properties immediately after generation
3. Use explicit types: Always specify subtype and format parameters
4. Monitor memory: Process large files in chunks if needed
5. Keep logs: Save verification results for debugging