Comuniqa : Exploring Large Language Models for improving speaking skills
Manas Mhasakar, Shikhar Sharma, Apurv Mehra, Utkarsh Venaik, Ujjwal, Singhal, Dhruv Kumar, Kashish Mittal

TL;DR
This paper introduces Comuniqa, an LLM-based system designed to improve English speaking skills, comparing its effectiveness with human expert feedback and highlighting its potential to enhance accessible language learning.
Contribution
The paper presents a novel LLM-based system, Comuniqa, for language learning, and evaluates its effectiveness against human expert guidance in improving speaking skills.
Findings
LLM-based system shows commendable accuracy in feedback
Comuniqa lacks human-level empathy and cognitive capabilities
System offers scalable and accessible language learning support
Abstract
In this paper, we investigate the potential of Large Language Models (LLMs) to improve English speaking skills. This is particularly relevant in countries like India, where English is crucial for academic, professional, and personal communication but remains a non-native language for many. Traditional methods for enhancing speaking skills often rely on human experts, which can be limited in terms of scalability, accessibility, and affordability. Recent advancements in Artificial Intelligence (AI) offer promising solutions to overcome these limitations. We propose Comuniqa, a novel LLM-based system designed to enhance English speaking skills. We adopt a human-centric evaluation approach, comparing Comuniqa with the feedback and instructions provided by human experts. In our evaluation, we divide the participants in three groups: those who use LLM-based system for improving speaking…
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Taxonomy
TopicsSpeech and dialogue systems · Intelligent Tutoring Systems and Adaptive Learning
