AI Tool for Linguistics & Psychometric Assessment of Soft Skills from Meeting Recordings Part. 2

Status: Completed

Project Duration: 10 Jun 2023 - 12 Aug 2023

Open Source resources available from this project

Project 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.

Omdena Hyderabad Local Chapter is working on a product that can evaluate meeting recordings and provide quantitative, personalized feedback on the soft skills of each participant along with recommendations to develop their skills throughout their professional journey.

A model for assessing communication skills from audio files and a framework for extracting byte-sized recommendations for various soft skills from online forums have been built as part of past local chapter challenges.

In order to get a holistic perspective of a person’s ability, it is important to consider the other essential soft skills such as interpersonal skills, leadership skills, adaptability, collaboration, empathy, critical thinking, conflict resolution, and time management. 

Assessment of the aforementioned soft skills from meeting recordings requires inputs from experts in domains such as linguistics and psychology to identify the different qualifying features that can be extracted from audio signals, mapped to appropriate soft skills, and fed to the machine learning pipeline built in past challenges.

Project goals.

The deliverables of this challenge include the development of audio-based linguistic and psychometric features specifically tailored for evaluating soft skills. These features will be integrated into a cohesive soft skill assessment pipeline. Additionally, a recommendation pipeline will be built to provide byte-sized recommendations based on the assessment results. These deliverables will provide organizations with valuable tools to objectively evaluate and enhance soft skills within their teams, fostering effective collaboration and achieving better results.

Project plan.

  • Week 1

    Data Collection and Exploratory Data Analysis

  • Week 2


  • Week 3

    Feature Extraction

  • Week 4

    Model Development and Training

  • Week 5

    ML Application

  • Week 6

    Model Integration & Deployment

Learning outcomes.

The Soft Skills Assessment Project is an AI system aimed at improving soft skills within organizations. It focuses on key aspects like effective communication, active listening, problem-solving, team building, and collaboration to enhance overall effectiveness. The project builds upon previous work, including a model for assessing communication skills and extracting recommendations for various soft skills. It aims to consider additional skills like leadership, adaptability, empathy, critical thinking, conflict resolution, and time management. Experts in linguistics and psychology collaborate to identify qualifying features from meeting recordings, which are then mapped to soft skills and used in a machine-learning pipeline.

The project is structured to be completed within 8 weeks and involves the following stages:
– Data Collection and Exploratory Data Analysis
– Preprocessing
– Feature Extraction
– Model Development and Training
– ML Application Model Integration & Deployment

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