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| | sdk: streamlit |
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| | # English Accent Detection Tool |
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| | ## Project Overview |
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| | This tool is a working proof-of-concept designed to evaluate spoken English in candidate video submissions. It automatically extracts audio from a public video or uploaded file, identifies whether the language spoken is English, and classifies the English accent (e.g., American, British, Australian). A confidence score is also provided to aid in candidate screening. |
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| | This submission was developed as part of the REM Waste hiring challenge, with emphasis on practicality, technical clarity, and clean design. |
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| | ## Features |
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| | * Accepts public video URLs (e.g., Loom, MP4 links) or uploaded video/audio files. |
| | * Extracts audio using `ffmpeg`. |
| | * Detects the spoken language using `SpeechBrain`'s language identification model. |
| | * If English is detected, simulates classification into common English accents. |
| | * Outputs include: |
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| | * Accent classification |
| | * Confidence score (0–100%) |
| | * Brief summary |
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| | --- |
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| | ## Live Demo |
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| | Deployed Streamlit app (hosted on Streamlit Cloud): |
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| | **\[Live App URL – Insert Link Here]** |
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| | ## Technology Stack |
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| | * **Python 3** |
| | * **Streamlit** for the web interface |
| | * **SpeechBrain** for spoken language identification |
| | * **Torchaudio** for audio preprocessing |
| | * **FFMPEG** for audio extraction |
| | * **Requests, Matplotlib** for I/O and optional output handling |
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| | --- |
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| | ## How It Works |
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| | 1. The user inputs a video URL or uploads a file. |
| | 2. The audio is extracted and resampled to a suitable format. |
| | 3. The system determines whether the speaker is using English. |
| | 4. If English is detected, the tool classifies the accent based on common linguistic traits. |
| | 5. The result includes: |
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| | * Accent label (e.g., British) |
| | * Confidence score |
| | * Explanation or notes |
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| | --- |
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| | ## Local Setup Instructions |
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| | 1. Clone the repository: |
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| | ```bash |
| | git clone https://github.com/yourusername/english-accent-detector.git |
| | cd english-accent-detector |
| | ``` |
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| | 2. Install dependencies: |
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| | ```bash |
| | pip install -r requirements.txt |
| | ``` |
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| | 3. Launch the app: |
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| | ```bash |
| | streamlit run app.py |
| | ``` |
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| | --- |
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| | ## Requirements |
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| | ``` |
| | streamlit |
| | torch |
| | torchaudio |
| | speechbrain |
| | ffmpeg-python |
| | requests |
| | matplotlib |
| | ``` |
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| | --- |
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| | ## Notes |
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| | * Accent classification is simulated based on common accent features, due to the lack of an open-source, fine-grained English accent classifier. |
| | * The core English language detection is handled by a pre-trained SpeechBrain model. |
| | * This project was developed as a rapid prototype within the recommended 4–6 hour window and can be expanded into a production-grade system with access to more detailed accent datasets and APIs. |
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| | --- |
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| | ## Author |
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| | Developed by Edgar Muyale |
| | For inquiries: edgarmuyale@gmail.com |
| | Submission for REM Waste Hiring Challenge |
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