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README.md
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---
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title: Music
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emoji: π΅
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colorFrom: indigo
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colorTo: purple
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@@ -8,40 +8,109 @@ sdk_version: 5.22.0
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app_file: app.py
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pinned: false
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license: mit
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short_description: AI music
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---
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# Music
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This
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- Simple and intuitive user interface
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##
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##
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title: Advanced Music Analysis & Beat-Matched Lyrics Generator
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emoji: π΅
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colorFrom: indigo
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colorTo: purple
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app_file: app.py
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pinned: false
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license: mit
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short_description: AI-powered music analysis with beat-synchronized lyrics generation
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---
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# Advanced Music Analysis & Beat-Matched Lyrics Generator
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This comprehensive AI-powered application provides advanced music analysis and generates perfectly synchronized lyrics that match the musical structure, rhythm, and emotional content of your audio files.
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## π― Key Features
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### πΌ **Comprehensive Music Analysis**
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- **Genre Classification**: Automatic detection using [dima806/music_genres_classification](https://huggingface.co/dima806/music_genres_classification)
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- **Tempo & Time Signature Detection**: Advanced multi-method analysis (4/4, 3/4, 6/8)
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- **Emotional Analysis**: 8-dimensional emotion detection (happy, sad, excited, calm, etc.)
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- **Thematic Analysis**: Identifies musical themes (love, triumph, loss, adventure, etc.)
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- **Tonal Analysis**: Key detection, mode analysis (major/minor), harmonic complexity
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- **Beat Pattern Analysis**: Precise beat tracking and stress pattern identification
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### π€ **Beat-Synchronized Lyrics Generation**
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- **Rhythm-Matched Lyrics**: Each line perfectly aligns with musical phrases and beat patterns
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- **Syllable-to-Beat Mapping**: Precise syllable counting and stress pattern matching
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- **Custom Requirements Integration**: Add your own creative directions and themes
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- **Genre-Specific Optimization**: Tailored for Pop, Rock, Country, Disco, and Metal
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- **Flow Analysis**: Ensures natural sentence flow across multiple lines
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- **Quality Metrics**: Detailed beat matching and syllable accuracy analysis
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### π¨ **Personalization Features**
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- **Custom Prompt Input**: Specify themes, imagery, perspective, style, or content requirements
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- **Intelligent Blending**: Merges your requirements with detected musical characteristics
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- **Flexible Creative Control**: From simple themes to complex narrative directions
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## π How It Works
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1. **Upload Audio**: Support for various audio formats, or record directly
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2. **Add Custom Requirements** (Optional): Specify your creative vision
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3. **Advanced Analysis**: Multi-layered analysis of musical characteristics:
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- Rhythm and tempo analysis
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- Time signature detection using autocorrelation, pattern matching, and spectral analysis
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- Emotional profiling using valence-arousal mapping
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- Thematic classification based on musical features
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- Beat pattern extraction and stress analysis
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4. **Lyrics Generation**: AI creates lyrics using [Qwen/QwQ-32B](https://huggingface.co/Qwen/QwQ-32B) that:
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- Match the detected beat patterns and time signature
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- Incorporate detected emotions and themes
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- Follow your custom creative requirements
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- Maintain proper syllable-to-beat ratios for the genre
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5. **Quality Analysis**: Comprehensive beat matching analysis with accuracy metrics
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## π΅ Supported Genres for Lyrics Generation
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**Full Support** (Analysis + Beat-Matched Lyrics):
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- **Pop**: Optimized syllable patterns and emotional expression
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- **Rock**: Energetic phrasing with strong beat emphasis
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- **Country**: Narrative flow with authentic storytelling patterns
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- **Disco**: Rhythmic momentum with dance-friendly phrasing
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- **Metal**: Intense expression with dramatic beat alignment
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**Analysis Only**: All other genres receive comprehensive musical analysis without lyrics generation.
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## π οΈ Technical Features
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### Advanced Analysis Algorithms
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- **Multi-Method Time Signature Detection**: Combines autocorrelation, pattern matching, spectral analysis, note density analysis, and tempo-based estimation
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- **Emotion Mapping**: 8-dimensional emotion space with valence-arousal coordinates
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- **Beat Strength Analysis**: Onset detection with energy and spectral flux analysis
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- **Syllable Stress Matching**: CMU Dictionary integration with rule-based fallback
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### AI-Powered Generation
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- **4-bit Quantization**: Efficient inference on T4 GPU using BitsAndBytesConfig
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- **Specialized Prompting**: Genre-aware prompt engineering for optimal results
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- **Quality Enforcement**: Automatic syllable limit enforcement and line count validation
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- **Flow Optimization**: Sentence continuation analysis for natural lyrical flow
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## π Analysis Outputs
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### Musical Analysis
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- Tempo (BPM) and time signature with confidence scores
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- Primary and secondary emotions with confidence percentages
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- Musical themes and their relevance scores
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- Key signature and mode detection
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- Beat pattern visualization
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### Lyrics Quality Metrics
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- Syllable-to-beat match accuracy
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- Stress pattern alignment scores
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- Sentence flow quality assessment
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- Genre-appropriate range compliance
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- Overall rhythmic accuracy percentage
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## π― Custom Requirements Examples
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**Themes**: "Write about a journey through mountains", "Focus on urban nightlife"
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**Imagery**: "Use ocean metaphors", "Include references to light and shadow"
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**Perspective**: "From a child's viewpoint", "Nostalgic memories", "Future aspirations"
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**Style**: "Conversational tone", "Include internal rhymes", "Simple everyday language"
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**Content**: "Avoid melancholy", "Include words 'freedom' and 'horizon'", "Focus on resilience"
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## π Model Credits
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- **Genre Classification**: [dima806/music_genres_classification](https://huggingface.co/dima806/music_genres_classification)
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- **Lyrics Generation**: [Qwen/QwQ-32B](https://huggingface.co/Qwen/QwQ-32B) with 4-bit quantization
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- **Audio Processing**: librosa, scipy, numpy for advanced signal processing
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- **Linguistic Analysis**: NLTK CMU Dictionary for syllable counting and stress analysis
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## πͺ Try It Now
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Experience the future of AI-powered music analysis and lyrics generation. Upload your music and watch as the system creates perfectly synchronized, emotionally resonant lyrics tailored to your creative vision!
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app.py
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music_analyzer = MusicAnalyzer()
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# Process uploaded audio file
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def process_audio(audio_file):
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if audio_file is None:
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return "No audio file provided", None, None, None, None, None, None, None, None, None
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# Generate lyrics only for supported genres
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if genre_supported:
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lyrics = generate_lyrics(music_analysis, primary_genre, duration)
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beat_match_analysis = analyze_lyrics_rhythm_match(lyrics, lyric_templates, primary_genre)
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else:
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supported_genres_str = ", ".join([genre.capitalize() for genre in beat_analyzer.supported_genres])
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print(error_msg)
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return error_msg, None, None, None, None, None, None, None, None, None
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def generate_lyrics(music_analysis, genre, duration):
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try:
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# Extract meaningful information for context
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tempo = music_analysis["rhythm_analysis"]["tempo"]
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min_syl_for_prompt = 2
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max_syl_for_prompt = 7
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-
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SONG DETAILS:
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- Key: {key} {mode}
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- Primary emotion: {primary_emotion}
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- Secondary emotion: {secondary_emotion}
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- Primary theme: {primary_theme}
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- Secondary theme: {secondary_theme}
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CRITICAL REQUIREMENTS (MOST IMPORTANT):
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- You MUST write EXACTLY {num_phrases_for_prompt} lines of lyrics.
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LYRICS:
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(Your {num_phrases_for_prompt} numbered lyric lines go here, each starting with its number, a period, and a space)
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Remember: Output EXACTLY {num_phrases_for_prompt} numbered lyric lines. Each line's content (after removing the number) must be {min_syl_for_prompt}-{max_syl_for_prompt} syllables.'''
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else:
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# Calculate the typical syllable range for this genre
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num_phrases_for_prompt = len(lyric_templates)
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max_syl_for_prompt = max([t.get('max_expected', 7) for t in lyric_templates]) if lyric_templates and lyric_templates[0].get('max_expected') else 7
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min_syl_for_prompt = min([t.get('min_expected', 2) for t in lyric_templates]) if lyric_templates and lyric_templates[0].get('min_expected') else 2
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SONG DETAILS:
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- Key: {key} {mode}
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- Primary emotion: {primary_emotion}
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- Secondary emotion: {secondary_emotion}
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- Primary theme: {primary_theme}
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- Secondary theme: {secondary_theme}
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CRITICAL REQUIREMENTS (MOST IMPORTANT):
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- You MUST write EXACTLY {num_phrases_for_prompt} lines of lyrics.
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LYRICS:
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(Your {num_phrases_for_prompt} numbered lyric lines go here, each starting with its number, a period, and a space)
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Remember: Output EXACTLY {num_phrases_for_prompt} numbered lyric lines. Each line's content (after removing the number) must be {min_syl_for_prompt}-{max_syl_for_prompt} syllables.'''
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# Generate with optimized parameters for QwQ model
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messages = [
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{"role": "user", "content": prompt}
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# Create Gradio interface
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def create_interface():
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with gr.Blocks(title="Music Analysis & Lyrics Generator") as demo:
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gr.Markdown("# Music Analysis & Lyrics Generator")
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gr.Markdown("Upload
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with gr.Row():
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with gr.Column(scale=1):
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audio_input = gr.Audio(
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label="Upload or Record Audio",
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type="filepath",
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sources=["upload", "microphone"]
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)
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with gr.Column(scale=2):
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with gr.Tab("Analysis"):
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analysis_output = gr.Textbox(label="Music Analysis Results", lines=10)
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with gr.Row():
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tempo_output = gr.Number(label="Tempo (BPM)")
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time_sig_output = gr.Textbox(label="Time Signature")
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with gr.Row():
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primary_emotion_output = gr.Textbox(label="Primary Emotion")
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secondary_emotion_output = gr.Textbox(label="Secondary Emotion")
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with gr.Row():
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primary_theme_output = gr.Textbox(label="Primary Theme")
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secondary_theme_output = gr.Textbox(label="Secondary Theme")
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genre_output = gr.Textbox(label="Primary Genre")
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with gr.Tab("Generated Lyrics"):
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lyrics_output = gr.Textbox(label="
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with gr.Tab("Beat Matching"):
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beat_match_output = gr.Markdown(label="
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# Set up event handlers
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analyze_btn.click(
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fn=process_audio,
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inputs=[audio_input],
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outputs=[
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analysis_output, lyrics_output, tempo_output, time_sig_output,
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primary_emotion_output, secondary_emotion_output,
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)
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# Format supported genres for display
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supported_genres_md = "\n".join([f"- {genre.capitalize()}" for genre in beat_analyzer.supported_genres])
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gr.Markdown(f"""
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## How
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{supported_genres_md}
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These genres have consistent syllable-to-beat patterns that work
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""")
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return demo
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music_analyzer = MusicAnalyzer()
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# Process uploaded audio file
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def process_audio(audio_file, custom_prompt=""):
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if audio_file is None:
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return "No audio file provided", None, None, None, None, None, None, None, None, None
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# Generate lyrics only for supported genres
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if genre_supported:
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lyrics = generate_lyrics(music_analysis, primary_genre, duration, custom_prompt)
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beat_match_analysis = analyze_lyrics_rhythm_match(lyrics, lyric_templates, primary_genre)
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else:
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supported_genres_str = ", ".join([genre.capitalize() for genre in beat_analyzer.supported_genres])
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print(error_msg)
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return error_msg, None, None, None, None, None, None, None, None, None
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def generate_lyrics(music_analysis, genre, duration, custom_prompt=""):
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try:
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# Extract meaningful information for context
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tempo = music_analysis["rhythm_analysis"]["tempo"]
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min_syl_for_prompt = 2
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max_syl_for_prompt = 7
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# Build the base prompt
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base_prompt = f'''You are a professional songwriter. Write song lyrics for a {genre} song.
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SONG DETAILS:
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- Key: {key} {mode}
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- Primary emotion: {primary_emotion}
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- Secondary emotion: {secondary_emotion}
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- Primary theme: {primary_theme}
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- Secondary theme: {secondary_theme}'''
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# Add custom requirements if provided
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custom_requirements = ""
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if custom_prompt and custom_prompt.strip():
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custom_requirements = f'''
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SPECIAL REQUIREMENTS FROM USER:
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{custom_prompt.strip()}
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Please incorporate these requirements while still following all the technical constraints below.'''
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prompt = base_prompt + custom_requirements + f'''
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CRITICAL REQUIREMENTS (MOST IMPORTANT):
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- You MUST write EXACTLY {num_phrases_for_prompt} lines of lyrics.
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LYRICS:
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(Your {num_phrases_for_prompt} numbered lyric lines go here, each starting with its number, a period, and a space)
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Remember: Output EXACTLY {num_phrases_for_prompt} numbered lyric lines. Each line's content (after removing the number) must be {min_syl_for_prompt}-{max_syl_for_prompt} syllables.'''
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else:
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# Calculate the typical syllable range for this genre
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num_phrases_for_prompt = len(lyric_templates)
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max_syl_for_prompt = max([t.get('max_expected', 7) for t in lyric_templates]) if lyric_templates and lyric_templates[0].get('max_expected') else 7
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min_syl_for_prompt = min([t.get('min_expected', 2) for t in lyric_templates]) if lyric_templates and lyric_templates[0].get('min_expected') else 2
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# Build the base prompt
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base_prompt = f'''You are a professional songwriter. Write song lyrics for a {genre} song.
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SONG DETAILS:
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- Key: {key} {mode}
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- Primary emotion: {primary_emotion}
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- Secondary emotion: {secondary_emotion}
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- Primary theme: {primary_theme}
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- Secondary theme: {secondary_theme}'''
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# Add custom requirements if provided
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322 |
+
custom_requirements = ""
|
323 |
+
if custom_prompt and custom_prompt.strip():
|
324 |
+
custom_requirements = f'''
|
325 |
+
|
326 |
+
SPECIAL REQUIREMENTS FROM USER:
|
327 |
+
{custom_prompt.strip()}
|
328 |
+
Please incorporate these requirements while still following all the technical constraints below.'''
|
329 |
+
|
330 |
+
prompt = base_prompt + custom_requirements + f'''
|
331 |
|
332 |
CRITICAL REQUIREMENTS (MOST IMPORTANT):
|
333 |
- You MUST write EXACTLY {num_phrases_for_prompt} lines of lyrics.
|
|
|
365 |
LYRICS:
|
366 |
(Your {num_phrases_for_prompt} numbered lyric lines go here, each starting with its number, a period, and a space)
|
367 |
|
368 |
+
Remember: Output EXACTLY {num_phrases_for_prompt} numbered lyric lines. Each line's content (after removing the number) must be {min_syl_for_prompt}-{max_syl_for_prompt} syllables.'''
|
369 |
# Generate with optimized parameters for QwQ model
|
370 |
messages = [
|
371 |
{"role": "user", "content": prompt}
|
|
|
856 |
|
857 |
# Create Gradio interface
|
858 |
def create_interface():
|
859 |
+
with gr.Blocks(title="Advanced Music Analysis & Beat-Matched Lyrics Generator") as demo:
|
860 |
+
gr.Markdown("# π΅ Advanced Music Analysis & Beat-Matched Lyrics Generator")
|
861 |
+
gr.Markdown("**Upload music to get comprehensive analysis and generate perfectly synchronized lyrics that match the rhythm, emotion, and structure of your audio**")
|
862 |
|
863 |
with gr.Row():
|
864 |
with gr.Column(scale=1):
|
865 |
audio_input = gr.Audio(
|
866 |
+
label="π§ Upload or Record Audio",
|
867 |
type="filepath",
|
868 |
sources=["upload", "microphone"]
|
869 |
)
|
870 |
+
|
871 |
+
# Add custom prompt input
|
872 |
+
custom_prompt_input = gr.Textbox(
|
873 |
+
label="π¨ Custom Lyrics Requirements (Optional)",
|
874 |
+
placeholder="e.g., 'Write about a rainy day in the city' or 'Include metaphors about flying' or 'Make it about overcoming challenges'",
|
875 |
+
lines=3,
|
876 |
+
info="Add any specific requirements, themes, or creative directions for the lyrics. This will be merged with the music analysis to create personalized lyrics."
|
877 |
+
)
|
878 |
+
|
879 |
+
analyze_btn = gr.Button("π Analyze Music & Generate Lyrics", variant="primary", size="lg")
|
880 |
|
881 |
with gr.Column(scale=2):
|
882 |
+
with gr.Tab("π Music Analysis"):
|
883 |
+
analysis_output = gr.Textbox(label="Comprehensive Music Analysis Results", lines=10)
|
884 |
|
885 |
with gr.Row():
|
886 |
+
tempo_output = gr.Number(label="π₯ Tempo (BPM)")
|
887 |
+
time_sig_output = gr.Textbox(label="β±οΈ Time Signature")
|
888 |
|
889 |
with gr.Row():
|
890 |
+
primary_emotion_output = gr.Textbox(label="π Primary Emotion")
|
891 |
+
secondary_emotion_output = gr.Textbox(label="π Secondary Emotion")
|
892 |
|
893 |
with gr.Row():
|
894 |
+
primary_theme_output = gr.Textbox(label="π Primary Theme")
|
895 |
+
secondary_theme_output = gr.Textbox(label="πͺ Secondary Theme")
|
896 |
+
genre_output = gr.Textbox(label="πΌ Primary Genre")
|
897 |
|
898 |
+
with gr.Tab("π€ Generated Lyrics"):
|
899 |
+
lyrics_output = gr.Textbox(label="Beat-Synchronized Lyrics", lines=20)
|
900 |
|
901 |
+
with gr.Tab("π― Beat Matching Analysis"):
|
902 |
+
beat_match_output = gr.Markdown(label="Rhythm & Syllable Synchronization Analysis")
|
903 |
|
904 |
# Set up event handlers
|
905 |
analyze_btn.click(
|
906 |
fn=process_audio,
|
907 |
+
inputs=[audio_input, custom_prompt_input],
|
908 |
outputs=[
|
909 |
analysis_output, lyrics_output, tempo_output, time_sig_output,
|
910 |
primary_emotion_output, secondary_emotion_output,
|
|
|
914 |
)
|
915 |
|
916 |
# Format supported genres for display
|
917 |
+
supported_genres_md = "\n".join([f"- **{genre.capitalize()}**: Optimized for {genre} music patterns" for genre in beat_analyzer.supported_genres])
|
918 |
|
919 |
gr.Markdown(f"""
|
920 |
+
## π How It Works
|
921 |
+
|
922 |
+
1. **π§ Upload Audio**: Support for various formats (MP3, WAV, etc.) or record directly in your browser
|
923 |
+
2. **π¨ Add Custom Requirements** (Optional): Specify your creative vision, themes, or style preferences
|
924 |
+
3. **π Advanced Analysis**: Multi-layered analysis including:
|
925 |
+
- **Tempo & Time Signature**: Advanced detection using multiple algorithms
|
926 |
+
- **Emotional Profiling**: 8-dimensional emotion mapping (happy, sad, excited, calm, etc.)
|
927 |
+
- **Thematic Analysis**: Musical themes (love, triumph, adventure, reflection, etc.)
|
928 |
+
- **Beat Pattern Extraction**: Precise rhythm and stress pattern identification
|
929 |
+
- **Genre Classification**: AI-powered genre detection with confidence scores
|
930 |
+
4. **π€ Lyrics Generation**: AI creates perfectly synchronized lyrics that:
|
931 |
+
- **Match Beat Patterns**: Each line aligns with musical phrases and rhythm
|
932 |
+
- **Follow Syllable Constraints**: Precise syllable-to-beat mapping for natural flow
|
933 |
+
- **Incorporate Emotions & Themes**: Blend detected musical characteristics
|
934 |
+
- **Include Your Requirements**: Merge your creative directions seamlessly
|
935 |
+
5. **π Quality Analysis**: Comprehensive metrics showing beat matching accuracy and flow quality
|
936 |
+
|
937 |
+
## π¨ Custom Requirements Examples
|
938 |
+
|
939 |
+
**π Themes**: "Write about nature and freedom", "Focus on urban nightlife", "Tell a story about friendship"
|
940 |
+
|
941 |
+
**πΌοΈ Imagery**: "Use ocean metaphors", "Include references to stars and sky", "Focus on light and shadow"
|
942 |
+
|
943 |
+
**ποΈ Perspective**: "From a child's viewpoint", "Make it nostalgic", "Focus on hope and resilience"
|
944 |
+
|
945 |
+
**βοΈ Style**: "Use simple everyday language", "Include some rhyming", "Make it conversational"
|
946 |
+
|
947 |
+
**π Content**: "Avoid sad themes", "Include words 'journey' and 'home'", "Focus on personal growth"
|
948 |
+
|
949 |
+
The system intelligently blends your requirements with detected musical characteristics to create personalized, rhythm-perfect lyrics.
|
950 |
+
|
951 |
+
## π΅ Supported Genres for Full Lyrics Generation
|
952 |
+
|
953 |
+
**β
Full Support** (Complete Analysis + Beat-Matched Lyrics):
|
954 |
{supported_genres_md}
|
955 |
|
956 |
+
These genres have consistent syllable-to-beat patterns that work optimally with our advanced rhythm-matching algorithm.
|
957 |
+
|
958 |
+
**π Analysis Only**: All other genres receive comprehensive musical analysis (tempo, emotion, themes, etc.) without lyrics generation.
|
959 |
+
|
960 |
+
## π οΈ Advanced Features
|
961 |
+
|
962 |
+
- **π― Beat Synchronization**: Syllable-perfect alignment with musical phrases
|
963 |
+
- **π§ Emotion Integration**: Lyrics reflect detected emotional characteristics
|
964 |
+
- **π Theme Incorporation**: Musical themes guide lyrical content
|
965 |
+
- **π Quality Metrics**: Detailed analysis of rhythm matching accuracy
|
966 |
+
- **π Flow Optimization**: Natural sentence continuation across lines
|
967 |
+
- **βοΈ Genre Optimization**: Tailored patterns for different musical styles
|
968 |
""")
|
969 |
|
970 |
return demo
|