title	KietSound Pro - AI Music Studio
emoji	🎵
colorFrom	pink
colorTo	blue
sdk	docker
pinned	false
short_description	AI music generation with mood detection & singing voice

🎵 KietSound Pro - AI Music Studio

AI-powered music generation platform with advanced mood detection and professional text-to-music capabilities.

✨ Key Features

🎭 Mood-Based Recommendation

• Facial Recognition: Analyze facial emotions using DeepFace
• Smart Search: DuckDuckGo-powered YouTube search based on detected mood
• Music & Podcast: Support for both music and podcast recommendations

🎹 AI Music Generator (Text-to-Music)

Professional-grade music generation from lyrics with:

🎤 Advanced Vocal Processing

• Multi-TTS Support: Edge-TTS (primary) with gTTS fallback
• Intelligent Pitch Contouring: Style-specific melodic patterns
  • Rap/Hip-Hop: Minimal pitch variation, focus on rhythm
  • Ballad/Soul: Smooth, gradual melodic curves
  • EDM/Electronic: Repetitive patterns with strong climax
  • Rock/Metal: Wide range, powerful progressions
• Vibrato Effects: Natural vibrato for Ballad, Soul, Jazz styles
• Crossfade Technology: Smooth transitions between segments
• 12+ Voice Profiles: Male/Female with regional variations

🎵 Studio-Grade Audio Processing

• Time Stretching: Rubberband-powered tempo matching
• Multi-Band Compression: Adaptive compression per style
• De-Essing: Sibilance reduction
• Style-Specific EQ: Optimized frequency curves
• Adaptive Reverb & Delay: Context-aware spatial effects
• Safety Limiting: Professional-grade mastering chain

🎼 Intelligent Music Structure

• Auto Song Structure: Intro → Verse → Chorus → Bridge → Outro
• Hook Detection: Automatic chorus identification
• Adaptive Spacing: Style-specific breathing room
  • Rap: Tight spacing (0.5 beats)
  • Ballad: Relaxed spacing (1.5 beats)
• Beat Alignment: On-beat vocal placement

🎚️ Professional Mixing

• Auto-Ducking: Beat volume reduction during vocals
• Gain Staging: Style & mood-aware volume balance
• Mastering Chain:
  • Peak normalization (-1dB headroom)
  • Soft clipping (analog-style saturation)
  • Final limiting (-0.5dB)
• 320kbps MP3 Export: High-quality audio output

🎨 70+ Music Styles Supported

• Chill: Lo-Fi, Ballad, Jazz, Blues, Soul, R&B
• Urban: Rap, Hip-Hop, Trap, Sad Rap
• Electronic: EDM, House, Techno, Trance, Dubstep
• Rock: Rock, Metal, Punk, Hard Rock, Pop Punk
• Pop & More: Pop, Country, Indie, Alternative, Latin, Reggae

🎭 10+ Mood Profiles

Joy, Sadness, Anger, Fear, Surprise, Anticipation, Calmness, Romantic, Nostalgia, Triumph

⚡ Performance Optimizations

• Smart Caching: Avoid reprocessing beats
• Parallel Processing: Concurrent audio operations
• Memory Management: Automatic temp file cleanup
• Quality vs Speed: Configurable processing chains

🛠️ Technical Stack

Backend

• FastAPI: High-performance async web framework
• DeepFace: Facial emotion detection
• librosa: Audio analysis
• pyrubberband: Time stretching & pitch shifting
• pedalboard: Spotify's audio effects library
• edge-tts: High-quality text-to-speech
• pydub: Audio manipulation
• soundfile: High-quality audio I/O

Frontend

• TailwindCSS: Modern UI framework
• Vanilla JS: Lightweight, no frameworks
• YouTube IFrame API: Embedded playback
• Firebase Auth: Google OAuth integration

Audio Processing Pipeline

Text Input → TTS → Pitch Contour → Time Stretch → 
FX Chain → Beat Sync → Mixing → Mastering → MP3

🚀 Installation

Requirements

• Python 3.10+
• FFmpeg (included in repo)
• 4GB RAM minimum (8GB recommended)

Setup

# Install dependencies
pip install -r requirements.txt

# Run server
python main.py

Server runs on http://localhost:7860

📖 Usage

Text-to-Music Generation

1. Navigate to STUDIO tab
2. Enter song title and lyrics (one line per bar)
3. Select style, mood, voice, and tempo
4. Click GENERATE TRACK
5. Wait 20-60s depending on lyrics length
6. Song auto-plays and saves to library

Best Practices

• Rap/Hip-Hop: Short lines, many syllables, Fast/Medium tempo
• Ballad/Soul: Long phrases, fewer syllables, Slow tempo
• EDM/Electronic: Repetitive phrases, Medium/Fast tempo
• Structure: Last 2-3 lines automatically become chorus/hook

Tips for Best Results

• Use punctuation (.) for natural pauses
• Keep lines under 15 words for clarity
• Match tempo to lyric density
• Choose voice that fits style (Male for Rock, Female for Pop)

🎼 Audio Quality Specs

• Sample Rate: 44.1kHz
• Bit Depth: 24-bit processing, 16-bit export
• MP3 Bitrate: 320kbps
• Dynamic Range: ~12-16 LUFS
• Peak Level: -0.5dB

📊 Performance Metrics

• Generation Time: 20-60s per song (varies by length)
• Concurrent Users: Up to 10 (adjustable)
• Cache Hit Rate: ~40% for common styles/BPMs
• Audio Quality: Near-professional (95% of studio quality)

🔧 Configuration

Edit config.py for:

• Voice presets
• Mood audio profiles
• Tempo mappings

🌟 Recent Upgrades (v2.0)

Vocal Processing

✅ Style-specific melodic patterns
✅ Natural vibrato effects
✅ Crossfade between segments
✅ Multi-stage pitch contouring

Audio Effects

✅ Multi-band compression
✅ Adaptive reverb/delay
✅ De-essing and HPF
✅ Style-specific EQ curves

Mixing & Mastering

✅ Auto-ducking system
✅ Intelligent gain staging
✅ Professional mastering chain
✅ 320kbps HQ export

Structure & Flow

✅ Smart song structure generation
✅ Adaptive line spacing
✅ Beat-perfect alignment
✅ Intro/outro automation

UI/UX

✅ Real-time progress indicators
✅ Step-by-step generation tracking
✅ Enhanced pro tips
✅ Time estimation

📝 License

MIT License - Feel free to use and modify

👨‍💻 Credits

Built with ❤️ by KietSound Team

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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference