Graphien

• 

  Landing-Dashboard

• GIF

  MVP

Inspiration

Inspired by the journey of learning Japanese through Duolingo, we discovered a gap in the language learning market: writing. Realizing the potential for a tool that focuses on teaching the art of writing in various languages, we envisioned Graphien. It's our answer to seamlessly extend the engaging experience of learning to speak a language to mastering its written form.

What it does

Graphien teaches users to write in multiple languages by guiding them in forming letters and words, then letting them practice directly in the app. Using convolutional neural networks, it evaluates the handwriting for accuracy, supporting freeform writing and adapting to different sizes and styles. This technology provides instant, personalized feedback, making learning to write in new languages both effective and engaging.

How we built it

We built Graphien by first developing a handwriting recognition model with a convolutional neural network, using a diverse dataset of handwritten characters. Then, we integrated this model with a seamless front-end for user interaction and a powerful back-end for quick processing, creating a low-latency, effective learning platform.

Challenges we ran into

Challenges we ran into

1. JavaScript Canvas Integration: Managing the canvas for handwriting input and converting these inputs into a model-friendly format was technically challenging, requiring precise adjustments to accurately capture and process the data.

2. Word-Level Recognition: Evolving the model to recognize entire words, not just individual letters, significantly increased complexity, necessitating advanced neural network solutions and a comprehensive dataset to ensure accurate and efficient word recognition.

Accomplishments that we're proud of

We successfully developed a smooth, user-friendly web application that operates with low latency, ensuring a seamless learning experience for users as they practice and improve their writing in multiple languages. This achievement is particularly gratifying given the technical challenges we overcame, showcasing our commitment to delivering a high-quality educational tool.

What we learned

We learned the comprehensive process of building a product around AI, from conceptualizing and developing a machine learning model to integrating it into a user-friendly application. This experience taught us the importance of balancing technical performance with usability, ensuring the AI not only functions effectively but also enhances the user experience.

What's next for Graphien

Our next steps involve expanding Graphien's capabilities to support multiple languages and advance from individual characters to full words. Additionally, we aim to embrace the art of calligraphy, offering users the chance to explore and learn various calligraphic styles. This expansion will make Graphien not just a tool for writing but a comprehensive platform for artistic and cultural expression through handwriting.

Built With

• css3
• flask
• html5
• javascript
• keras
• python
• tensorflow