Update README.md

README.md

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+
 ---
-title: Audio Analyzer
-emoji: 😻
-colorFrom: yellow
-colorTo: pink
+title: Audio Forensic Analyzer
+emoji: 🎵
+colorFrom: blue
+colorTo: purple
 sdk: gradio
-sdk_version: 6.0.2
+sdk_version: 4.0.0
 app_file: app.py
 pinned: false
-short_description: 'Detailed audio analyzer '
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# 🎵 Audio Forensic Analyzer
+
+Comprehensive audio quality analysis tool with automatic detection of compression, filtering, clipping, and spectral anomalies.
+
+## Features
+
+✅ **Comprehensive Analysis**
+- Time-domain statistics (peak, RMS, crest factor, SNR)
+- Spectral analysis (centroid, bandwidth, rolloff)
+- Energy distribution across frequency bands
+- Integrated loudness (LUFS) measurement
+
+✅ **Automatic Detection**
+- Digital clipping
+- Over-compression and limiting
+- High-pass/Low-pass filtering
+- Brick-wall filters
+- Spectral notches
+
+✅ **Professional Reports**
+- High-quality PNG report with spectrogram
+- Energy distribution charts
+- Quality scoring (A-F grades)
+- Saved as `{filename}_report.png` in `reports/` folder
+
+## How to Use
+
+1. Upload an audio file (WAV, MP3, FLAC, OGG, M4A, AAC)
+2. Click "Analyze Audio" or wait for auto-analysis
+3. View the comprehensive report and download it
+
+## Report Contents
+
+- **Spectrogram:** Visual frequency representation
+- **File Info:** Sample rate, channels, duration
+- **Time-Domain:** Peak/RMS levels, crest factor, SNR
+- **Spectral Stats:** Frequency distribution and rolloffs
+- **Energy Chart:** Bar chart of frequency bands
+- **Issues:** Automatic problem detection with severity levels
+- **Quality Score:** Overall grade (A-F) and score (0-100)
+
+Reports are automatically saved in the `reports/` folder with your original filename + `_report.png` suffix.