Karol Wegner, a co-founder and board member of itCraft, decided to develop a new mobile application that would revolutionize the language learning industry. He found a problem to solve and believed that Flutter is a perfect technology to build a solution. With the support of our design and development team, we’ve created the MVP of the product. itCraft also became the initial investor for BeeSpeaker.
An innovative language learning solution with voice recognition, gamified to give the users more motivation to learn foreign languages.
PL | Education
Creating a mobile application that would help the users with their talking skills. Most language apps on the market focus on reading and writing, but speech is crucial in everyday life. We had to create a digital product that would allow people to learn words, sentences and idioms in a convenient, easy way.
BeeSpeaker is a native speaker in one’s pocket, and there was a huge demand for it from the day the first, basic MVP was shown to the public. Now its full-on MVP version is available in app stores and it receives positive reviews. We are still working on the product to eliminate any potential defects, make it scalable for multiple future users and add more features to make it a full solution for both lecturers and students. There are many plans to expand this project and we will work on it, as it’s a true language learning revolution!
At first, we’ve decided to create an MVP which was a Flutter-based, cross-platform app for Android and iOS. It needed a machine learning implementation with voice technologies on board to give the users an opportunity to watch lessons and answer questions or repeat sentences.
We’ve created a digital product that has a lot to offer.
It’s an innovative language learning solution with voice recognition,
gamified to give the users more motivation to learn foreign languages.
It uses the natural approach in teaching, which means the students have to listen,
repeat and answer questions asked by native speakers in pre-recorded video lessons.
The app can determine if the user is saying it right or wrong and ask for another try if there are any mistakes.
The app is available on Android and iOS.
In this project, we took an approach based on a lot of testing. We shared the prototype of an app early on to verify it with usersand find out if the market is interested in such a solution. When we had our proof that indeed there is a problem we can fix, we’ve decided to develop the app further.
We’ve formed a team of specialists, including UX and UI designers, developers, testers and more to prepare the app. Simultaneously, we had our lecturers record the first lessons to be implemented in the app. Our machine learning expert prepared everything that was required to create a voice recognition solution that would make the software understand, what the user is speaking.
Every iteration we had more and more work to do, and each time we were consulting our results with real language learners to find out if that’s what they expect.