## Inspiration

People want music ubiquitously. Plenty of playlists exist for showering, studying, and working out - so why don't we generate a playlist from text by analyzing the emotions from it? **Notes for Notes** generates music playlists for the book that you will be reading tonight. It can understand your youtube video just by reading the transcript and then recommend the background music just for your video. It can take in a scene from a movie script and give you the soundtrack to live the moment as you read it. Wouldn’t video editing be much more dynamic?

## What it does

First, choose a file that contains text. It can be a jpeg, jpg, or png file, which means our application will recognize characters from the photo of handwritings too! Then, the Natural Language Understanding will go through advanced text analysis, yielding emotion keywords and conceptual keywords, all with their respective levels of confidence. Using those keywords, we analyzed their connotations and co-occurrences of topics in order to associate them to Spotify genres in order of importance. Finally, using those genres, we yielded your top Spotify playlists to represent your text.

## How we built it

We used \_ Google Cloud OCR(optical character recognition) API \_ to recognize a text from jpg, jpeg, png. For emotion analysis, we used \_ IBM Watson’s Natural Language Understanding API \_. From the result, we used the Spotify API to generate playlists. Finally, we used Vue.js framework for Frontend and NodeJS for backend to make the web application.

## Challenges we ran into

The first challenge was to connect the existing APIs to our local machines. Since we haven't dealt with this many API in one web application before, it was difficult to be brave at first. Yet we figured out this part by asking a lot of questions and watching youtube tutorials!

The second was that Spotify API doesn't support the recommendation fully since that is one of the most popular features of Spotify. Also, the authorization for Spotify API was very tricky. This prevented us from using our original design.

## Accomplishments that we're proud of

*We did it !*

## What we learned

1. Web application-related knowledge. One of our teammates learned javascript here!
2. Linguistic analysis

## What's next for Notes for Notes

**Expansion:** We would like to be able to work up to an implementation where one could scroll through the text in real time and see how the generated playlists change as the storyline evolves! They could also track which genres dominate which parts of the text, and examine the patterns and relationships between those genres. We would also be interested in a multimodal approach that does not only utilize text but expands its computer vision applications to a movie or show; in others words, the combination of the analysis of what's on the screen would be in combination with the script/text analysis to generate an even more representative playlist.

**A new B2B model for media companies:** This is perfect timing for media companies to use **Notes for Notes**. Link metadata to the music that goes well with their products. Advertisement, Trailers, and even E-books, the possibilities are endless.

**Work in reverse!:** If we discover enough patterns from textual concepts to musical genres, we can perhaps go in reverse to analyze a song and predict what kinds of themes a text related to that song would pertain to. Considering the popularity that movie soundtracks and lucrative artists can bring to media, it would be useful to take the most popular genres of music and see what kinds of movies/show/texts would create the ultimate marketable compatibility.
## Inspiration

After considering what hackathon project to pursue, our team, JAKT, encountered a common obstacle that visually impaired individuals face: their struggle with interacting with technology and our dynamic society. While there are existing solutions, they are expensive, bulky, and therefore inaccessible to many. Text2Touch is our take on the Braille Display combining our implementation of the Braille Display through computer text & computer vision. This versatility, along with its accessibility, is what we would like to bring to the community in hopes of providing the visually impaired with a new, cheaper, and more environmentally friendly way of interacting with our dynamic world.

## What it does

Text2Touch takes a screen's text, downloads as a txt file, and parses the text into serial data that then is sent over to an Arduino and reinterpreted as braille.

## How we built it

Our initial plan was to 3D print the parts that make up the electromagnets' chassis. However, our parts (as of 10:26 AM), have not been printed yet. Thus, we utilized aluminum cans, recycled cardboard, and clean paper food wrappings to create our ECO-FRIENDLY prototype of the braille display.

We split off to tackle the firmware, hardware and software components of this project. Our firmware was coded on the Arduino IDE, our hardware was glued, taped, soldered, and tested to completion, and our software was programmed with Python and Javascript. In the end, we came together to debug and combine our efforts into a tangible prototype that we're extremely excited to share!

## Challenges we ran into

There were many setbacks involving the hardware, chassis construction, and library utilization in our software. However, we tried to do the best we could through our dedicated teamwork and debugging efforts.

## Accomplishments that we're proud of

We're proud that we utilized relays to construct our electromagnets, that we persevered with our chassis despite the lack of technical and inventory limitations, and that we were able to accomplish the volume of work in 24 hours.

## What's next for Text2Touch

We want to refine Text2Touch to create a seamless user experience. We will do so by possibly implementing text-to-speech, refining our camera-to-touch feature, and improving the interactions between our Chrome Extension, the Arduino, and the Text2Touch Braille Display.
## Inspiration ✨

Seeing friends' lives being ruined through **unhealthy** attachment to video games. Struggling with regulating your emotions properly is one of the **biggest** negative effects of video games.

## What it does 🍎

YourHP is a webapp/discord bot designed to improve the mental health of gamers. By using ML and AI, when specific emotion spikes are detected, voice recordings are queued *accordingly*. When the sensor detects anger, calming reassurance is played. When happy, encouragement is given, to keep it up, etc.

The discord bot is an additional fun feature that sends messages with the same intention to improve mental health. It sends advice, motivation, and gifs when commands are sent by users.

## How we built it 🔧

Our entire web app is made using Javascript, CSS, and HTML. For our facial emotion detection, we used a javascript library built using TensorFlow API called FaceApi.js. Emotions are detected by what patterns can be found on the face such as eyebrow direction, mouth shape, and head tilt. We used their probability value to determine the emotional level and played voice lines accordingly.

The timer is a simple build that alerts users when they should take breaks from gaming and sends sound clips when the timer is up. It uses Javascript, CSS, and HTML.

## Challenges we ran into 🚧

Capturing images in JavaScript, making the discord bot, and hosting on GitHub pages, were all challenges we faced. We were constantly thinking of more ideas as we built our original project which led us to face time limitations and was not able to produce some of the more unique features to our webapp. This project was also difficult as we were fairly new to a lot of the tools we used. Before this Hackathon, we didn't know much about tensorflow, domain names, and discord bots.

## Accomplishments that we're proud of 🏆

We're proud to have finished this product to the best of our abilities. We were able to make the most out of our circumstances and adapt to our skills when obstacles were faced. Despite being sleep deprived, we still managed to persevere and almost kept up with our planned schedule.

## What we learned 🧠

We learned many priceless lessons, about new technology, teamwork, and dedication. Most importantly, we learned about failure, and redirection. Throughout the last few days, we were humbled and pushed to our limits. Many of our ideas were ambitious and unsuccessful, allowing us to be redirected into new doors and opening our minds to other possibilities that worked better.

## Future ⏭️

YourHP will continue to develop on our search for a new way to combat mental health caused by video games. Technological improvements to our systems such as speech to text can also greatly raise the efficiency of our product and towards reaching our goals!