Inspiration
We recognized that access to quality language learning resources for Tibetan is limited, and we wanted to create a tool that would help both beginners and advanced learners immerse themselves in the language. By leveraging technology, we aim to make learning Tibetan more accessible and engaging for people worldwide.
What it does
Our app offers a comprehensive learning experience for anyone interested in learning Tibetan. It features interactive lessons, speech recognition for pronunciation practice, and a variety of exercises to reinforce vocabulary and grammar. Through a combination of audio, visual, and text-based materials, users can progress from basic phrases to more complex conversations, all at their own pace.
How we built it
The front-end was developed with React.js to ensure a smooth and responsive user experience, while the back-end was powered by Flask, allowing us to handle requests and manage data efficiently. For speech recognition, we integrated a pre-trained Wav2Vec2 model tailored for Tibetan speech,
Challenges we ran into
designing the app to be both educational and engaging required careful consideration of user experience and content presentation. We also faced logistical challenges,
Accomplishments that we're proud of
we managed to create an intuitive and user-friendly interface that makes language learning accessible to people of all ages and backgrounds. The app’s ability to combine modern technology with cultural education is a testament to our commitment to both innovation and tradition.
What we learned
We gained valuable experience in machine learning, especially in adapting models for specific linguistic challenges. Additionally, this project reinforced the importance of teamwork and communication, as we had to collaborate closely to overcome technical and creative hurdles.
What's next for team 6
Looking ahead, Team 6 plans to expand the app’s capabilities by adding more advanced language features, such as conversational AI and personalized learning paths. We also aim to gather more data to further refine the speech recognition model, making it even more accurate and responsive.
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