Onomi

Inspiration

I give English tutoring lessons, and vocabulary is one of the most important components of learning a new language. Even though some people are at a certain level in English, improving their vocabulary can take them to the next level. It's hard to just look through a dictionary and learn new words, so an app that helps with this can be beneficial.

What it does

Onomi lets you scan your environment and find objects. Through the English names of the objects, people can learn new vocabulary without translation. This means there's no need to memorize the translation of a word, since people only need the object and its name. Through sentence examples, people can strengthen their memory, and with the test feature, they can test what they've learned.

How I built it

I'm used to developing apps with React Native, so I chose this specific stack. With the help of Claude, I built a system that scans the environment, detects objects through Apple's built-in object detector, and saves them to local memory. It's also worth noting that the app can be used fully offline, as it is entirely client-side.

Challenges I ran into

Detecting objects through an AI model is not an easy task. Initially, I considered using other models for object detection that had better accuracy, but they would have been more costly and harder to implement. So I settled on Apple's built-in object detector and leveraged it to work best with the current setup. Even though it isn't perfect, it works well enough to meet the requirements.

Accomplishments that I'm proud of

Making the app fully client-side.

What I learned

Sometimes there's a simpler way of doing things, we shouldn't over-engineer everything.

What's next for Onomi

There are a lot of features I still want to implement. I want Onomi to be more than just an education tool. Through collecting words, I want to gamify the experience more and make it more fun for people to learn new words. I also definitely want to improve the detection algorithm in the future.

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