## Inspiration

There are many scary things in the world ranging from poisonous spiders to horrifying ghosts, but none of these things scare people more than the act of public speaking. Over 75% of humans suffer from a fear of public speaking but what if there was a way to tackle this problem? That's why we created Strive.

## What it does

Strive is a mobile application that leverages voice recognition and AI technologies to provide instant actionable feedback in analyzing the voice delivery of a person's presentation. Once you have recorded your speech Strive will calculate various performance variables such as: voice clarity, filler word usage, voice speed, and voice volume. Once the performance variables have been calculated, Strive will then render your performance variables in an easy-to-read statistic dashboard, while also providing the user with a customized feedback page containing tips to improve their presentation skills. In the settings page, users will have the option to add custom filler words that they would like to avoid saying during their presentation. Users can also personalize their speech coach for a more motivational experience. On top of the in-app given analysis, Strive will also send their feedback results via text-message to the user, allowing them to share/forward an analysis easily.

## How we built it

Utilizing the collaboration tool Figma we designed wireframes of our mobile app. We uses services such as Photoshop and Gimp to help customize every page for an intuitive user experience. To create the front-end of our app we used the game engine Unity. Within Unity we sculpt each app page and connect components to backend C# functions and services. We leveraged IBM Watson's speech toolkit in order to perform calculations of the performance variables and used stdlib's cloud function features for text messaging.

## Challenges we ran into

Given our skillsets from technical backgrounds, one challenge we ran into was developing out a simplistic yet intuitive user interface that helps users navigate the various features within our app. By leveraging collaborative tools such as Figma and seeking inspiration from platforms such as Dribbble, we were able to collectively develop a design framework that best suited the needs of our target user.

## Accomplishments that we're proud of

Creating a fully functional mobile app while leveraging an unfamiliar technology stack to provide a simple application that people can use to start receiving actionable feedback on improving their public speaking skills. By building anyone can use our app to improve their public speaking skills and conquer their fear of public speaking.

## What we learned

Over the course of the weekend one of the main things we learned was how to create an intuitive UI, and how important it is to understand the target user and their needs.

## What's next for Strive - Your Personal AI Speech Trainer

* Model voices of famous public speakers for a more realistic experience in giving personal feedback (using the Lyrebird API).
* Ability to calculate more performance variables for a even better analysis and more detailed feedback
## Inspiration

It is nearly a year since the start of the pandemic and going back to normal still feels like a distant dream.
As students, most of our time is spent attending online lectures, reading e-books, listening to music, and playing online games. This forces us to spend immense amounts of time in front of a large monitor, clicking the same monotonous buttons.

Many surveys suggest that this has increased the anxiety levels in the youth.

Basically, we are losing the physical stimulus of reading an actual book in a library, going to an arcade to enjoy games, or play table tennis with our friends.

## What it does

It does three things:
1) Controls any game using hand/a steering wheel (non-digital) such as Asphalt9

2) Helps you zoom-in, zoom-out, scroll-up, scroll-down only using hand gestures.

3) Helps you browse any music of your choice using voice commands and gesture controls for volume, pause/play, skip, etc.

## How we built it

The three main technologies used in this project are:

1) Python 3
The software suite is built using Python 3 and was initially developed in the Jupyter Notebook IDE.

2) OpenCV
The software uses the OpenCV library in Python to implement most of its gesture recognition and motion analysis tasks.

3) Selenium
Selenium is a web driver that was extensively used to control the web interface interaction component of the software.

## Challenges we ran into

1) Selenium only works with google version 81 and is very hard to debug :(

2) Finding the perfect HSV ranges corresponding to different colours was a tedious task and required me to make a special script to make the task easier.

3) Pulling an all-nighter (A coffee does NOT help!)

## Accomplishments that we're proud of

1) Successfully amalgamated computer vision, speech recognition and web automation to make a suite of software and not just a single software!

## What we learned

1) How to debug selenium efficiently
2) How to use angle geometry for steering a car using computer vision
3) Stabilizing errors in object detection

## What's next for E-Motion

I plan to implement more components in E-Motion that will help to browse the entire computer and make the voice commands more precise by ignoring background noise.
## Inspiration

The inspiration behind our project stems from the personal challenges we’ve faced in the past with public speaking and presentations. Like many others, we often found ourselves feeling overwhelmed by nerves, shaky voices, and the pressure of presenting in front of peers.
This anxiety would sometimes make it difficult to communicate ideas effectively, and the fear of judgment made the experience even more daunting. Recognizing that we weren’t alone in these feelings, we wanted to create a solution that could help others overcome similar hurdles.
That’s where Vocis comes in. Its aim is to give people the freedom and the ability to practice their presentation skills at their own pace, in a safe, supportive environment. Whether it’s practicing for a school project, a work presentation, or simply building the confidence to speak in front of others, the platform allows users to refine their delivery.

## What It Does

Our project aims to simulate real-life challenges that presenters might face. For example, handling difficult situations like Q&A sessions, dealing with hecklers, or responding to aggressive viewers. By creating these simulated scenarios, our software prepares users for the unpredictability of live presentations.
We hope that by giving people the tools and the settings to practice on their own terms, they can gradually build the skills and self-assurance needed to present with ease in any setting.

## Tech Stack - How Vocis is built

ReactJs
Shadcn
NextJs
TailwindCSS
Hume.Ai
OpenAI

## Challenges We Faced

During our hackathon, one of the key challenges we faced was the need to dive into extensive documentation while working on API implementation as we had never worked with Hume before. Not only that, as all of us don’t have much experience with the backend of an app, it was really taxing to learn and implement at the same time. This task, which is already time-consuming, became more difficult due to unstable internet connectivity. This led to unexpected delays in accessing resources and troubleshooting problems in real time, which put additional pressure on our timeline. Despite these setbacks, our team worked hard to adapt and maintain momentum.

## Accomplishments

Despite the challenges we faced, we were able to make a functional prototype at the very least that displays the core of our program which is simulating real-life difficult scenarios for presenters and public-speakers. At least, the very bare bones and we’re very proud of ourselves for being able to do that and create a wonderful project.

## What We Learned

We learned to create a viable project in limited time allowing us to overcome our shortcomings in our ability to create a project
Through multiple workshops and gaining insightful help from mentors, we learned more about APIs, implementing APIs, and making sure they cooperate with each other and streamlining the process.
We also learned a lot of new, cool and amazing technologies created by a lot of amazing people that allowed us to achieve the aim of our project

## What’s Next For Vocis

We allow multiple users to present at the same time and the AI can create situations for multiple “panelists”
We allow many more situations that panelists and presenters may face like many different types of aggressive people, journalists that are a little too overbearing.
We add reactions of the audience that is listening to our presentation so that it creates a more realistic experience for the user (“presenter”)
More security measure
Authentication