## Inspiration

The internet sparked an era of democratization with music-now its production follows. Smoothee's ML insights on music networks will help bring together the most desired collaborations and projects. Automation will consolidate artist copyrights, contributions and compensation. It is the ultimate artist credition platform - providing upcoming artists (those who do not have the backing of a huge label) with talent-sourcing, ML backed collaborative networks, the ability to contribute and get compensated directly for their effort.

## Features

* Sign in using local authentication, Instagram or Google. \* Search for your other creators \* Chat with your fellow creators in real-time. \* Like and comment on a feed. \* API for developers (under-development) \* View your/others profile. \* Follow a particular artist and get notified for his/her activities. \* Change your profile picture, bio, people who follow you etc. \* Find people with similar music thanks to TensorFlow Magenta (currently beta/ML)

## How-we-built-it

We used node.js, html and css with ejs for the webapp. For the music analyzer and collaborative networking tool, we relied on TensorFlow's Magenta library to match artists with similar music taste and also boost synergies between artists. We are still building our payments-acceptance system using the community Stripe API and Microsoft's BlockChain Service to ensure faster and safer payments. The whole webapp is hosted on Azure.

## Challenges we ran into

Our first iteration of the project idea was to help artists maintain and track collaborations for songs or larger projects. That, however, led to a discussion of how music was now an entirely digital and social medium. However, it still seemed like an LA exclusive deal. Some of it made sense. Having a dense network of creators led to better creations. But we knew a network like that didn't have to rely on established music labels. With ML, we could connect artists through their actual music. Creation could be natural and easy, with us taking care of the logistics of publishing and collaborating. We decided on a lofty purpose--to democratize music production and provide better music for all.

## Accomplishments-that-we're-proud-of

Our whole webapp - given that this is our first time at a hackathon.

## What we learned

A lot tbh
# Bryan

Your friendly note taking assistant

## Inspiration 💡

Our main inspiration for Bryan stemmed from the challenges we faced as students trying to **keep up with fast-paced lectures**. Taking **effective notes** while also **paying attention** to the professor can be daunting, and we wanted to create a solution that benefits all students, especially those with accessibility issues who may find it challenging to take notes in real-time. We aimed to enhance the learning experience by providing a **tool that accurately takes notes**, allowing students to focus on understanding the material rather than struggling with note-taking mid-lecture.

## What it does 🤖

Bryan is your study buddy in class. It accurately transcribes the professor's lectures and takes notes on it in real time. The notes are formatted in the readable Markdown file format, and bolds/italics relevant points. This format can be easily exported and stored for future use.

## How we built it 🔨

We began the project by using **PyAudio** to capture live audio. We then configured OpenAI's **Whisper** model to filter out background noise and generate a near real-time transcript of the audio. After that, we fine tuned a **GPT-3.5** model to convert transcribed speech to markdown format. Finally, we combined and integrated all of these elements into a **PyGame** application using **multithreading** to reduce delay in the note generation as much as possible. The user is able to save both the transcribed text and the generated markdown notes after the session is over.

## Challenges we ran into 🚩

1. We challenged ourselves to use PyGame for the UI, rather than a standard website. To do so, we had to create our own markdown renderer, which required a lot of tuning to ensure the text always aligns with the lined paper, among other challenges.
2. We also faced difficulties **filtering out background noise** from the audio input. We originally wanted to use Google Cloud for speech recognition, but we had to switch to OpenAI Whisper so we could clean up the audio quickly using the artificial neural network.
3. Another challenge involved **converting transcripts to notes in real-time while continuing to record audio**. To avoid gaps in audio recording, we opted to write to two temporary audio files. The first file is written to for the initial 10 seconds. Once 10 seconds elapse, we promptly initiate another thread to resume recording on the second file. Simultaneously, we halt the recording for the first file and upload it to OpenAI. This approach enables us to seamlessly capture audio while also segmenting it into manageable 10 second fragments.
4. After completing each of our respective tasks, we encountered a final challenge: **integrating everything together**. We had to engage in extensive debugging as we encountered numerous unexpected problems, possibly attributed to our lack of sleep.

## Accomplishments that we're proud of ⭐

We're proud of creating something that we as students can actually use in class to help improve our learning and productivity. We're also very proud of leveraging PyGame to render our front end. We stepped outside of our comfort zone to learn something new at this hackathon. Rendering markdown manually was very difficult, but we managed to pull it off.

## What we learned 📚

We learned the benefits of trying new things, such as Pygame, as it allowed us to learn and grow as developers. Above all, we learned the value of taking the time to find a truly compelling idea, something we ourselves could use.

## What's next for Bryan 🚀

* Making Bryan **more accessible** by deploying it to a website.
* Fine tuning with **more data**.
* **Styling options** for the notebook, such as font and color.
* Another LLM pass through the entire notebook after the presentation has concluded to **increase accuracy**.
* Integrate **images** into the note taking software.
## Inspiration

The idea for VenTalk originated from an everyday stressor that everyone on our team could relate to; commuting alone to and from class during the school year. After a stressful work or school day, we want to let out all our feelings and thoughts, but do not want to alarm or disturb our loved ones. Releasing built-up emotional tension is a highly effective form of self-care, but many people stay quiet as not to become a burden on those around them. Over time, this takes a toll on one’s well being, so we decided to tackle this issue in a creative yet simple way.

## What it does

VenTalk allows users to either chat with another user or request urgent mental health assistance. Based on their choice, they input how they are feeling on a mental health scale, or some topics they want to discuss with their paired user. The app searches for keywords and similarities to match 2 users who are looking to have a similar conversation. VenTalk is completely anonymous and thus guilt-free, and chats are permanently deleted once both users have left the conversation. This allows users to get any stressors from their day off their chest and rejuvenate their bodies and minds, while still connecting with others.

## How we built it

We began with building a framework in React Native and using Figma to design a clean, user-friendly app layout. After this, we wrote an algorithm that could detect common words from the user inputs, and finally pair up two users in the queue to start messaging. Then we integrated, tested, and refined how the app worked.

## Challenges we ran into

One of the biggest challenges we faced was learning how to interact with APIs and cloud programs. We had a lot of issues getting a reliable response from the web API we wanted to use, and a lot of requests just returned CORS errors. After some determination and a lot of hard work we finally got the API working with Axios.

## Accomplishments that we're proud of

In addition to the original plan for just messaging, we added a Helpful Hotline page with emergency mental health resources, in case a user is seeking professional help. We believe that since this app will be used when people are not in their best state of minds, it's a good idea to have some resources available to them.

## What we learned

Something we got to learn more about was the impact of user interface on the mood of the user, and how different shades and colours are connotated with emotions. We also discovered that having team members from different schools and programs creates a unique, dynamic atmosphere and a great final result!

## What's next for VenTalk

There are many potential next steps for VenTalk. We are going to continue developing the app, making it compatible with iOS, and maybe even a webapp version. We also want to add more personal features, such as a personal locker of stuff that makes you happy (such as a playlist, a subreddit or a netflix series).