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Case Study

Provided an AI-Based Solution for Assessing Oral Fluency for a Leading Publisher

Key Result Highlights

  • Reduced the time and effort for evaluation significantly.
  • More accurate and consistent results than the previous manual evaluation system.
  • The interface was user-friendly, simple, and intuitive.
  • Easy system navigation for non-technical users.

The Client

The client is one of the most renowned publishing companies globally.

The Challenge

The client wanted to integrate a reliable and efficient assessment system to assess the oral fluency of non-native English speakers. Their existing system was time-consuming and relied on manual evaluation, making it prone to errors and inconsistencies.

Critical Success Factors

    • Find an AI system with ability to accurately evaluate oral fluency, including factors like pronunciation, grammar, vocabulary, and intonation.
    • The flexibility to accommodate a diverse range of accents and dialects.
    • User-friendliness and easy navigation.

Our Approach

    • Researched and identified multiple solutions available in the market and reviewed how each solution utilized Natural Language Processing (NLP) and Machine Learning (ML) techniques.
    • Adopted an AI-based assessment tool consisting of two components: a speech recognition system and a scoring engine.
    • The speech recognition system utilized NLP techniques to transcribe spoken words into text.
    • The scoring engine employed ML algorithms to evaluate the text according to predefined criteria and generate a score.

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