In the spirit of AthenaHacks, we were motivated to work on an app relevant to issues that women disproportionally face. We were inspired to create this app after learning women generally tend to present themselves less confidently than men, which can affect others' impressions of them and their own self-image. With the help of our cheerful mascot Hera, we aim to help anyone and everyone appear more professional and poised in their lives.

What it does

The app records your voice and analyzes it for "qualifiers" aka words and phrases that can make you sound less confident and authoritative. You can add custom qualifiers, and Hoots with Hera will present a summary of how many times you've said each quantifier after you've finished your speech. Hoots with Hera will also encourage you by letting you know if you used fewer quantifiers than your last speech. There is also a built in stopwatch for those who'd like to practice timed speeches.

How we built it

We built Hoot with Hera in Swift using XCode, and took advantage of several frameworks such as AVFoundation, AVAudioSession, and AFNetworking.

Challenges we ran into

Because many APIs provide client SDKs for Objective-C and not Swift (what we were more experienced in), we needed to work with new ways to accomplish the implementation goals we had.

Accomplishments that we're proud of

We're proud to present an app that encourages us to discuss (literally) about how we speak, and the way our language choice affects how confident we appear to other people and how we judge ourselves. Additionally, we're excited to present an app where we both had a hand in creating a UI that is aesthetically pleasing and UX that is easy for users to understand and use.

What we learned

We learned how to use many new frameworks that improved our project, and made it possible. We also learned about how even knowing about qualifying language forced us to omit these words and phrases from our everyday dialogue.

What's next for Hoots with Hera

We'd like to be able to collect even more data and to use machine learning to analyze the data. We believe that given a larger data set, we'd be able to refine the app in order to help users improve their language

We'd also like to add gamification and social aspects within the app, in order to make the app an even more engaging user experience. We also plan to make Hera smarter, by implementing NLP APIs to categorize the data that we collect, and give the user further insight into their speech practice.

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