Spaces:
Sleeping
Sleeping
adding config
Browse files
Info.md
ADDED
@@ -0,0 +1,249 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# English Accent Detection Tool
|
2 |
+
|
3 |
+
A practical AI tool that analyzes English accents from video content. Built for REM Waste's hiring automation system.
|
4 |
+
|
5 |
+
## 🚀 Live Demo
|
6 |
+
|
7 |
+
**Deployed App:** [https://accent-detector.streamlit.app](https://accent-detector.streamlit.app)
|
8 |
+
|
9 |
+
## Features
|
10 |
+
|
11 |
+
- **Video Processing**: Accepts public video URLs (MP4, Loom, etc.)
|
12 |
+
- **Audio Extraction**: Automatically extracts audio from video files
|
13 |
+
- **Speech Transcription**: Converts speech to text using Google Speech Recognition
|
14 |
+
- **Accent Analysis**: Detects English accents with confidence scoring
|
15 |
+
- **Web Interface**: Simple Streamlit UI for easy testing
|
16 |
+
|
17 |
+
## Supported Accents
|
18 |
+
|
19 |
+
- American English
|
20 |
+
- British English
|
21 |
+
- Australian English
|
22 |
+
- Canadian English
|
23 |
+
- South African English
|
24 |
+
|
25 |
+
## Quick Start
|
26 |
+
|
27 |
+
### Method 1: Use the Deployed App (Recommended)
|
28 |
+
|
29 |
+
1. Visit: [https://accent-detector.streamlit.app](https://accent-detector.streamlit.app)
|
30 |
+
2. Paste a public video URL
|
31 |
+
3. Click "Analyze Accent"
|
32 |
+
4. View results with confidence scores
|
33 |
+
|
34 |
+
### Method 2: Local Installation
|
35 |
+
|
36 |
+
```bash
|
37 |
+
# Clone or download the script
|
38 |
+
git clone <repository-url>
|
39 |
+
cd accent-detector
|
40 |
+
|
41 |
+
# Install dependencies
|
42 |
+
pip install -r requirements.txt
|
43 |
+
|
44 |
+
# Install ffmpeg (required for video processing)
|
45 |
+
# On macOS:
|
46 |
+
brew install ffmpeg
|
47 |
+
|
48 |
+
# On Ubuntu/Debian:
|
49 |
+
sudo apt update && sudo apt install ffmpeg
|
50 |
+
|
51 |
+
# On Windows:
|
52 |
+
# Download from https://ffmpeg.org/download.html
|
53 |
+
|
54 |
+
# Run the app
|
55 |
+
streamlit run accent_detector.py
|
56 |
+
```
|
57 |
+
|
58 |
+
## Installation
|
59 |
+
|
60 |
+
1. Clone this repository and navigate to the project folder.
|
61 |
+
2. (Recommended) Create and activate a Python virtual environment:
|
62 |
+
```sh
|
63 |
+
python3 -m venv ad_venv
|
64 |
+
source ad_venv/bin/activate
|
65 |
+
```
|
66 |
+
3. Install all dependencies:
|
67 |
+
```sh
|
68 |
+
pip install -r requirements.txt
|
69 |
+
```
|
70 |
+
4. (Optional, but recommended for better performance) Install Watchdog:
|
71 |
+
```sh
|
72 |
+
xcode-select --install # macOS only, for build tools
|
73 |
+
pip install watchdog
|
74 |
+
```
|
75 |
+
|
76 |
+
## Usage Examples
|
77 |
+
|
78 |
+
### Test URLs
|
79 |
+
```
|
80 |
+
# Direct MP4 link
|
81 |
+
https://sample-videos.com/zip/10/mp4/SampleVideo_1280x720_1mb.mp4
|
82 |
+
|
83 |
+
# Loom video (public)
|
84 |
+
https://www.loom.com/share/your-video-id
|
85 |
+
|
86 |
+
# Google Drive (public)
|
87 |
+
https://drive.google.com/file/d/your-file-id/view
|
88 |
+
```
|
89 |
+
|
90 |
+
### Expected Output
|
91 |
+
```json
|
92 |
+
{
|
93 |
+
"accent": "American",
|
94 |
+
"confidence": 78.5,
|
95 |
+
"explanation": "High confidence in American accent with strong linguistic indicators.",
|
96 |
+
"all_scores": {
|
97 |
+
"American": 78.5,
|
98 |
+
"British": 23.1,
|
99 |
+
"Australian": 15.7,
|
100 |
+
"Canadian": 19.2,
|
101 |
+
"South African": 8.3
|
102 |
+
}
|
103 |
+
}
|
104 |
+
```
|
105 |
+
|
106 |
+
## Technical Architecture
|
107 |
+
|
108 |
+
### Core Components
|
109 |
+
|
110 |
+
1. **Video Downloader**: Downloads videos from public URLs
|
111 |
+
2. **Audio Extractor**: Uses ffmpeg to extract WAV audio
|
112 |
+
3. **Speech Recognizer**: Google Speech Recognition API
|
113 |
+
4. **Accent Analyzer**: Pattern matching for linguistic markers
|
114 |
+
5. **Web Interface**: Streamlit-based UI
|
115 |
+
|
116 |
+
### Accent Detection Algorithm
|
117 |
+
|
118 |
+
The system analyzes multiple linguistic features:
|
119 |
+
|
120 |
+
- **Vocabulary Patterns**: Accent-specific word choices
|
121 |
+
- **Phonetic Markers**: Pronunciation characteristics
|
122 |
+
- **Spelling Patterns**: Regional spelling differences
|
123 |
+
- **Linguistic Markers**: Characteristic phrases and expressions
|
124 |
+
|
125 |
+
### Confidence Scoring
|
126 |
+
|
127 |
+
- **0-20%**: Insufficient markers detected
|
128 |
+
- **21-50%**: Moderate confidence with limited indicators
|
129 |
+
- **51-75%**: Good confidence with multiple patterns
|
130 |
+
- **76-100%**: High confidence with strong linguistic evidence
|
131 |
+
|
132 |
+
## API Integration
|
133 |
+
|
134 |
+
For programmatic access, use the core `AccentDetector` class:
|
135 |
+
|
136 |
+
```python
|
137 |
+
from accent_detector import AccentDetector
|
138 |
+
|
139 |
+
detector = AccentDetector()
|
140 |
+
result = detector.process_video("https://your-video-url.com/video.mp4")
|
141 |
+
|
142 |
+
print(f"Accent: {result['accent']}")
|
143 |
+
print(f"Confidence: {result['confidence']}%")
|
144 |
+
```
|
145 |
+
|
146 |
+
## Deployment
|
147 |
+
|
148 |
+
### Streamlit Cloud (Recommended)
|
149 |
+
|
150 |
+
1. Fork this repository
|
151 |
+
2. Connect to Streamlit Cloud
|
152 |
+
3. Deploy from your GitHub repo
|
153 |
+
4. Share the public URL
|
154 |
+
|
155 |
+
### Docker Deployment
|
156 |
+
|
157 |
+
```dockerfile
|
158 |
+
FROM python:3.9-slim
|
159 |
+
|
160 |
+
# Install system dependencies
|
161 |
+
RUN apt-get update && apt-get install -y ffmpeg
|
162 |
+
|
163 |
+
WORKDIR /app
|
164 |
+
COPY requirements.txt .
|
165 |
+
RUN pip install -r requirements.txt
|
166 |
+
|
167 |
+
COPY . .
|
168 |
+
EXPOSE 8501
|
169 |
+
|
170 |
+
CMD ["streamlit", "run", "accent_detector.py", "--server.port=8501", "--server.address=0.0.0.0"]
|
171 |
+
```
|
172 |
+
|
173 |
+
## Limitations & Considerations
|
174 |
+
|
175 |
+
### Current Limitations
|
176 |
+
- Requires clear speech audio (background noise affects accuracy)
|
177 |
+
- Works best with 30+ seconds of speech
|
178 |
+
- Free Google Speech Recognition has daily limits
|
179 |
+
- Accent detection based on vocabulary/patterns, not phonetic analysis
|
180 |
+
|
181 |
+
### Potential Improvements
|
182 |
+
- Integrate phonetic analysis libraries
|
183 |
+
- Add more accent varieties (Indian, Irish, etc.)
|
184 |
+
- Implement batch processing for multiple videos
|
185 |
+
- Add voice activity detection for better audio segmentation
|
186 |
+
|
187 |
+
## Testing
|
188 |
+
|
189 |
+
### Manual Testing
|
190 |
+
1. Test with different accent samples
|
191 |
+
2. Verify confidence scores are reasonable
|
192 |
+
3. Check error handling with invalid URLs
|
193 |
+
4. Test with various video formats
|
194 |
+
|
195 |
+
### Automated Testing
|
196 |
+
```python
|
197 |
+
def test_accent_detection():
|
198 |
+
detector = AccentDetector()
|
199 |
+
|
200 |
+
# Test American accent
|
201 |
+
american_text = "I'm gonna grab some cookies from the elevator"
|
202 |
+
scores = detector.analyze_accent_patterns(american_text)
|
203 |
+
assert scores['American'] > scores['British']
|
204 |
+
|
205 |
+
# Test British accent
|
206 |
+
british_text = "That's brilliant, quite lovely indeed"
|
207 |
+
scores = detector.analyze_accent_patterns(british_text)
|
208 |
+
assert scores['British'] > scores['American']
|
209 |
+
```
|
210 |
+
|
211 |
+
## Performance Metrics
|
212 |
+
|
213 |
+
- **Video Download**: ~10-30 seconds (depends on file size)
|
214 |
+
- **Audio Extraction**: ~5-15 seconds
|
215 |
+
- **Speech Recognition**: ~10-30 seconds
|
216 |
+
- **Accent Analysis**: <1 second
|
217 |
+
- **Total Processing**: ~30-90 seconds per video
|
218 |
+
|
219 |
+
## Troubleshooting
|
220 |
+
|
221 |
+
### Common Issues
|
222 |
+
|
223 |
+
**Error: "Could not understand the audio"**
|
224 |
+
- Solution: Ensure clear speech, minimal background noise
|
225 |
+
|
226 |
+
**Error: "Failed to download video"**
|
227 |
+
- Solution: Verify URL is public and accessible
|
228 |
+
|
229 |
+
**Error: "ffmpeg not found"**
|
230 |
+
- Solution: Install ffmpeg system dependency
|
231 |
+
|
232 |
+
**Low confidence scores**
|
233 |
+
- Solution: Ensure longer speech samples (30+ seconds)
|
234 |
+
|
235 |
+
### Support
|
236 |
+
|
237 |
+
For technical issues or feature requests:
|
238 |
+
1. Check the error messages in the Streamlit interface
|
239 |
+
2. Verify all dependencies are installed correctly
|
240 |
+
3. Test with known working video URLs
|
241 |
+
|
242 |
+
## License
|
243 |
+
|
244 |
+
MIT License - Free for commercial and personal use.
|
245 |
+
|
246 |
+
---
|
247 |
+
|
248 |
+
**Built for REM Waste Interview Challenge**
|
249 |
+
*Practical AI tools for automated hiring decisions*
|
README.md
CHANGED
@@ -1,3 +1,14 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
# English Accent Detection Tool
|
2 |
|
3 |
A practical AI tool that analyzes English accents from video content. Built for REM Waste's hiring automation system.
|
|
|
1 |
+
---
|
2 |
+
title: English Accent Detector
|
3 |
+
emoji: 🎤
|
4 |
+
colorFrom: blue
|
5 |
+
colorTo: purple
|
6 |
+
sdk: streamlit
|
7 |
+
sdk_version: "1.28.0"
|
8 |
+
app_file: app.py
|
9 |
+
pinned: false
|
10 |
+
---
|
11 |
+
|
12 |
# English Accent Detection Tool
|
13 |
|
14 |
A practical AI tool that analyzes English accents from video content. Built for REM Waste's hiring automation system.
|