As students, we were faced with the issue of complex, fast-paced lectures which did not leave us time to write notes and pay attention.

What it does

It transforms speech to text, storing the transcripts. Also, it has a chatbot which answers users' lecture-related questions, offering keywords, definitions, dates or searches from the web.

How we built it

Using Objective-C, Microsoft Azure and DialogFlow.

Challenges we ran into

The first few attempts when we wanted to use Alexa instead of a chatbot. Choosing the right technologies that fit our team the best.

Accomplishments that we're proud of

Having come up with a useful idea and making it work in less than 24 hours. Building a smart chatbot that is intelligent enough to understand the key points of the lecture.

What we learned

How to use Microsoft Azure's solutions.

What's next for MQuill

Bringing lectures from different classes together to build a knowledge base that the chatbot uses to answer complex questions. Train the chatbot on the fly during the transcription of the lecture. Additionally, store the discussions with the chatbot, make it available on iPad.

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