Lingo Test Confidence Booster With AI Helping Learners Improve Spoken English Through Real Time AI Feedback

Public speaking is a vital skill for academic and professional success, yet numerous learners struggle with glos- sophobic bia, limited vocabulary, and weak delivery. Being training approaches, similar to practices or peer evaluation, give limited feedback and aren't scalable. This paper introduces Lingo-Test,an AI-powered platform designed to enhance spoken English through real-time, multimodal feedback. The system integrates Automatic Speech Recognition(ASR), Natural Lan- guage Processing(NLP), aspect discovery, and facial expression analysis to estimate both verbal and non-verbal performance. Unlike conventional tools that concentrate only on pronunciation or alphabet, Lingo-Test generates a compound confidence score and individualized recommendations covering ignorance, tone variation, vocabulary precarious, and eye contact. The architec- ture includes modular factors for speech processing, sentiment analysis, and feedback visualization, making it scalable for aca- demic and professional operations. An pilot study with learners indicated measurable advancements in ignorance, confidence, and non-verbal delivery. These results punctuate the eventuality of AI- driven multimodal feedback systems to reduce anxiety, strengthen tone mindfulness, and ameliorate communication chops, situatingLingo-Test as a practical result for education and training.\\n\\n

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-01-01
DOI
https://doi.org/10.5281/zenodo.19285045
Primary Topic
Emotion and Mood Recognition
Type
article
Field-Weighted Citation Impact
0.00
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article

Lingo Test Confidence Booster With AI Helping Learners Improve Spoken English Through Real Time AI Feedback

Rabindra Kumar Mahato, Rabindra Kaji Thapa, S. B. Patel, Bikee Kumar Sah et al.
Zenodo (CERN European Organization for Nuclear Research)
Emotion and Mood Recognition
article

Lingo Test Confidence Booster With AI Helping Learners Improve Spoken English Through Real Time AI Feedback

Rabindra Kumar Mahato, Rabindra Kaji Thapa, S. B. Patel, Bikee Kumar Sah, Nidhi Patel
article en

Abstract

Public speaking is a vital skill for academic and professional success, yet numerous learners struggle with glos- sophobic bia, limited vocabulary, and weak delivery. Being training approaches, similar to practices or peer evaluation, give limited feedback and aren't scalable. This paper introduces Lingo-Test,an AI-powered platform designed to enhance spoken English through real-time, multimodal feedback. The system integrates Automatic Speech Recognition(ASR), Natural Lan- guage Processing(NLP), aspect discovery, and facial expression analysis to estimate both verbal and non-verbal performance. Unlike conventional tools that concentrate only on pronunciation or alphabet, Lingo-Test generates a compound confidence score and individualized recommendations covering ignorance, tone variation, vocabulary precarious, and eye contact. The architec- ture includes modular factors for speech processing, sentiment analysis, and feedback visualization, making it scalable for aca- demic and professional operations. An pilot study with learners indicated measurable advancements in ignorance, confidence, and non-verbal delivery. These results punctuate the eventuality of AI- driven multimodal feedback systems to reduce anxiety, strengthen tone mindfulness, and ameliorate communication chops, situatingLingo-Test as a practical result for education and training.\\n\\n

Zenodo (CERN European Organization for Nuclear Research)
Quality Education
Openalex Percentile: Top 6%
Emotion and Mood Recognition
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