InclusiSphere

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What it does:*

InclusiSphere is a transformative web application designed to address various challenges faced during online conferences. It employs AI-powered solutions to promote diversity, inclusivity, and a safe environment in virtual conference settings. The application analyzes conversations, detects interruptions, identifies harassment, and assesses the sentiment of interactions. It generates a Cumulative Inclusivity Promotion (CIP) score for each participant, offering insights into their behavior and interactions, ultimately fostering equal opportunities, collaboration, and innovation.

How we built it:*

InclusiSphere was developed using a combination of technologies. The tech stack includes Django for backend development, machine learning libraries for AI-powered features, HTML, CSS, and Bootstrap for frontend design. The application utilizes a speech detection model to capture transcripts and audio data, which then pass through layers of processing involving profanity-check, interruption detection model, and sentiment analysis. The results from each layer are combined to generate the CIP score, which is used for individual profiling.

Challenges we ran into:*

During the development of InclusiSphere, the team faced several challenges:

Creating accurate interruption and ignorance detection models based on audio data.
Implementing real-time sentiment analysis to assess the tone of conversations.
Integrating multiple machine learning models into a cohesive system.
Ensuring the accuracy of the CIP score as a reflection of inclusivity.

Accomplishments that we're proud of:*

The team achieved several accomplishments with InclusiSphere:

Successfully developing and integrating various AI models to address specific challenges in online conferences.
Creating a user-friendly interface that allows participants to engage with the application seamlessly.
Designing an effective profiling system using the CIP score to provide valuable insights into participants' behavior and interactions.
Crafting a compelling narrative in the script to explain the application's purpose and impact.

What we learned:*

The development of InclusiSphere provided the team with valuable insights:

Improved understanding of speech recognition and audio data processing techniques.
Practical experience in implementing real-time sentiment analysis for nuanced interactions.
Enhancing proficiency in using Django for backend development and integrating machine learning models.
Gained insights into addressing diversity and inclusion challenges in online environments.

What's next for InclusiSphere:*

Moving forward, the team plans to continue refining and enhancing InclusiSphere:

Expanding the application's features to encompass more aspects of diversity and inclusion.
Fine-tuning the AI models to improve accuracy and effectiveness in identifying various challenges.
Incorporating user feedback to enhance the user experience and meet evolving conference needs.
Exploring opportunities to integrate more advanced machine learning techniques and technologies for better insights and impact.

InclusiSphere's journey involves continuous growth and refinement as it strives to create a more inclusive and empowering conference experience for all participants.