## Inspiration

Social anxiety for many is an issue that plagues their day to day lives. Due to the lingering effects of COVID-19's mass social isolation, people everywhere find it hard to reconnect. Impromptu is a method of speech that challenges one to form meaningful presentations on the spot, often a major exercise in mock trial preparations. This is where we came up with **Guppy**, the **virtual** **speech** **companion**. Guppy trains you to become a master at the art of communication. The act of impromptu speech presents itself in job interviews, wedding toast, keynote events, or just plain talking with your friends! We wanted to find a project that any one of all ages can benefit from, including use in education, corporate, social, and personal environments. We want Guppy to help reunite the world!

## What it does

Guppy uses AI to create randomized prompts for the user to read and respond to, providing a new medium for practicing speech and communication.

## How we built it

We used conda, python, and most importantly, openAi.

## Challenges we ran into

We initially had a larger vision but overestimated the amount of time we had to fully execute our plan. As it was half of our first hackathons, the plethora of new knowledge being thrown at us was a bit overwhelming.

## Accomplishments that we're proud of

We all met for the first time today and are proud of effectively communicating to solidify a product design that appeals to all of us.

## What we learned

As first time hackers, we learned new technical skills such as developing a front end, using canva, and implementations of new AI technology.

## What's next for Guppy

In future iteration of Guppy we defiantly want to integrate Hume Ai's API into our project to better gauge confidence, tone, and expression. We also want to integrate motion detection and video to track eye movement, posture and mannerisms. Another key thing is making Guppy more tailored towards specific audiences such as younger children, or hardened professionals.
## Inspiration

We were inspired by two key challenges: the widespread anxiety around presentations among students and the unique difficulties faced by people with hearing disabilities in developing effective presentation skills. Recognizing that 75% of students fear presentations and that individuals with hearing impairments struggle to self-correct their speech patterns, we saw an opportunity to create an inclusive tool that empowers both groups to overcome these challenges.

## What it does

VoiceEdge AI is an AI-powered speech skills coach tailored for high school and college students, as well as individuals with hearing disabilities. It provides:

* Real-time feedback on speech patterns, rhythm, intonation, body language, and content delivery
* Personalized coaching to improve storytelling and persuasive skills
* Real-time practice sessions with your role model
* Visual cues and haptic feedback for users with hearing disabilities
* A safe, judgment-free environment for practice and skill development
* Adaptive learning that caters to different presentation scenarios and user needs
* Mindfulness techniques to help reduce stress and anxiety and build confidence for presentations

## How we built it

Test the API on the backend. Local computer we tested out the unit tests and
Semantic used the whisper API. Acoustic used the Praat.

## Challenges we ran into

We ran into problems with our computers not having the specified libraries, often running into ModuleNotFound errors. When trying to import HumeVoiceClient from the Hume library, we run into this problem. We solved this by using Google Colab instead of our local machines. By doing so, we were able to collaborate with one another on the project and work harmoniously. Debugging these issues meant that we had to spend time looking into forums and documentation. In addition, we also had problems with our access codes. We sought help by going into the Slack channels and using the redeem codes that they provided in the chat. By redeeming the free credits, we were able to focus on building the project and not having to worry about the billing.

## Accomplishments that we're proud of

Democratizing Role Models: Leveraged AI to make learning from role models accessible and widespread, reducing the scarcity of real-life mentors.
AI for Good: Integrated mindfulness techniques to help users manage stress and anxiety, enhancing their presentation skills.
Advanced Feedback: Utilized Hume's speech recognition and large language models (LLMs) like OpenAI and AWS Claude to provide clear, actionable feedback, making it easier for students to improve their skills.

## What's next for VoiceEdge AI

1. Streamline Product (1 Month):
2. Transition to a fully online platform with real-time feedback capabilities
3. Optimize system performance to reduce latency for a smoother user experience
4. User Research & NPO Collaboration (3 Months):
5. Conduct comprehensive user behavior analysis by recruiting diverse students
6. Partner with non-profit organizations to engage with hearing-impaired users
7. Test and refine business models based on feedback from NPO collaborations
8. Ecosystem & Feature Expansion (6 Months):
9. Develop an inclusive, engaging ecosystem featuring interactive avatars (e.g., teddy bears) to create a more welcoming practice environment
10. Introduce new modules for networking skills and small talk practice
11. Expand the platform's capabilities to cater to a wider range of communication scenarios
12. Continuous Improvement:
13. Regularly update our AI models based on user data and feedback
14. Enhance accessibility features for users with hearing disabilities
15. Explore partnerships with educational institutions to integrate VoiceEdge AI into curricula
16. Community Building:
17. Create a supportive user community for peer feedback and shared experiences
18. Organize virtual events and workshops to foster engagement and skill development
19. Research and Development:
20. Invest in ongoing research to improve AI coaching capabilities
21. Explore emerging technologies to enhance the user experience and effectiveness of the platform
## Inspiration

More money, more problems.
Lacking an easy, accessible, and secure method of transferring money? Even more problems.

An interesting solution to this has been the rise of WeChat Pay, allowing for merchants to use QR codes and social media to make digital payments.

But where does this leave people without sufficient bandwidth? Without reliable, adequate Wi-Fi, technologies like WeChat Pay and Google Pay simply aren't options. People looking to make money transfers are forced to choose between bloated fees or dangerously long wait times.

As designers, programmers, and students, we tend to think about how we can design tech. But how do you design tech for that negative space? During our research, we found of the people that lack adequate bandwidth, 1.28 billion of them have access to mobile service. This ultimately led to our solution: **Money might not grow on trees, but Paypayas do.** 🍈

## What it does

Paypaya is an SMS chatbot application that allows users to perform simple and safe transfers using just text messages.

Users start by texting a toll free number. Doing so opens a digital wallet that is authenticated by their voice. From that point, users can easily transfer, deposit, withdraw, or view their balance.

Despite being built for low bandwidth regions, Paypaya also has huge market potential in high bandwidth areas as well. Whether you are a small business owner that can't afford a swipe machine or a charity trying to raise funds in a contactless way, the possibilities are endless.

Try it for yourself by texting +1-833-729-0967

## How we built it

We first set up our Flask application in a Docker container on Google Cloud Run to streamline cross OS development. We then set up our database using MongoDB Atlas. Within the app, we also integrated the Twilio and PayPal APIs to create a digital wallet and perform the application commands. After creating the primary functionality of the app, we implemented voice authentication by collecting voice clips from Twilio to be used in Microsoft Azure's Speaker Recognition API.

For our branding and slides, everything was made vector by vector on Figma.

## Challenges we ran into

Man. Where do we start. Although it was fun, working in a two person team meant that we were both wearing (too) many hats. In terms of technical problems, the PayPal API documentation was archaic, making it extremely difficult for us figure out how to call the necessary functions. It was also really difficult to convert the audio from Twilio to a byte-stream for the Azure API. Lastly, we had trouble keeping track of conversation state in the chatbot as we were limited by how the webhook was called by Twilio.

## Accomplishments that we're proud of

We're really proud of creating a fully functioning MVP! All of 6 of our moving parts came together to form a working proof of concept. All of our graphics (slides, logo, collages) are all made from scratch. :))

## What we learned

Anson - As a first time back end developer, I learned SO much about using APIs, webhooks, databases, and servers. I also learned that Jacky falls asleep super easily.

Jacky - I learned that Microsoft Azure and Twilio can be a pain to work with and that Google Cloud Run is a blessing and a half. I learned I don't have the energy to stay up 36 hours straight for a hackathon anymore 🙃

## What's next for Paypaya

More language options! English is far from the native tongue of the world. By expanding the languages available, Paypaya will be accessible to even more people. We would also love to do more with financial planning, providing a log of previous transactions for individuals to track their spending and income. There are also a lot of rough edges and edge cases in the program flow, so patching up those will be important in bringing this to market.