Challenge background
We live in the knowledge economy and skills are your card. Some estimates state that 50% of the jobs will be affected due to automation by 2030. Non-routine cognitive skills, often described as “soft skills”, have been increasing in importance since the first industrial revolution. Soft skills have the potential to provide the only long-term competitive advantage in the job market of the future, and open up equal opportunities to culturally-diverse remote employees. At the same time, soft skills are the hardest to learn due to their abstract nature and context-dependency. The traditional coaching platforms are unscalable by design. Online learning marketplaces and MOOCs provide content that does not stick. Self-improvement apps add up to daily distractions and fail to maintain engagement.
Edtech Startup is a tech-enabled skill development tool for companies, aimed to help engineers get skills, like self-confidence, self-awareness, empathy, communication, influencing, taking ownership, with the use of technology. Edtech is going to connect all the learning tools & knowledge sources by automatically fetching user’s content, recommendations and insights into the Edtech learning pipeline. Then, it will help users act on them in the context of their life through a customizable mix of tools e.g., spaced-out notifications, self-reflection, community Q&As, speed-dating with peers. To put it in more context, we provide one source of truth around soft skills with a repository of resources, definitions and recipes on achieving goals.
The problem
Building on the previous two challenges, this project aims to create an AI system that can identify problem areas in the user’s interpersonal communication skills and recommend resources for improvement. So far we have built a pipeline that ingests user audio data and identifies possible weaknesses in their communication skills and a database of AI-curated tips. The current challenge will focus on integrating the two systems into a coherent whole. We will build a recommender system using Google Cloud Platform and work to improve the audio pipeline using insights drawn from our database of tips. We will also ensure the security of the system by training a GAN for user identification.
Goal of the project
Speech processing Combining Speech & Text Model Model building Using GANs in Speech Model (Generative AI modeling) Model deployment Recommender systems
Project timeline
- 1
Week 1
Week 1 - 2 : Understanding the Problem Statement and Data Collection, Data Preparation & exploring Pre-Trained ASR , Text Models.
- 2
Week 2
Week 3 - 4 : Model Training/Fine Tuning Pre-trained model, Finalizing the Model
- 3
Week 3
Week 5 - 7 : We will explore other possibilities such as data mining,Text analysis, Recommender Systems, Generative AI etc.
- 4
Week 4
Model Deployment on GCP/Streamlit