https://github.com/melau-eddy/shulevoice
An Offline IoT-Based Voice Learning Tool
https://github.com/melau-eddy/shulevoice
django-rest-framework esp32 lama microcontroller python3 raspberry-pi rest-api
Last synced: 4 months ago
JSON representation
An Offline IoT-Based Voice Learning Tool
- Host: GitHub
- URL: https://github.com/melau-eddy/shulevoice
- Owner: melau-eddy
- Created: 2025-09-24T07:14:40.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2025-09-24T08:01:37.000Z (4 months ago)
- Last Synced: 2025-09-24T09:35:14.212Z (4 months ago)
- Topics: django-rest-framework, esp32, lama, microcontroller, python3, raspberry-pi, rest-api
- Language: HTML
- Homepage:
- Size: 146 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
1. Device and System Design
• The learning tool will be built using Raspberry Pi or similar hardware.
• It will include a microphone and speaker for voice input and output.
• Speech recognition and synthesis will be handled by offline software tools such as Vosk and
eSpeak.
• The device will use a local database to store session data and learner progress.• Power options will include USB charging and support for solar input to suit off-grid
environments.
2. Content and Interaction Flow
• The system will present educational exercises through spoken prompts.
• Learners will respond verbally, and the system will evaluate and reply using voice.
• Exercises will be aligned to early primary school topics in English, Math, and Science.
• All interactions will be generated dynamically; no pre-recorded lessons or external audio
files will be used.
3. Web-Based Monitoring Dashboard
• An online platform will allow educators and caregivers to:
• View learner activity logs (e.g., time spent, topics attempted, responses).
• Sync progress data from the device when internet becomes available.
• Apply updates to content logic or system settings as needed.
• The platform is optional for daily use but enables improved tracking and remote
management.
4. Pilot Testing
• A pilot phase will be conducted in 3–5 rural schools.
• Observations and feedback will be collected on:
• Usability of the device by young children
• Accuracy of speech recognition and voice clarity
• Navigation flow and engagement during interaction
• Insights will guide final refinements before broader deployment.