2025
ACL
ACL 2025
Towards a Real-time Swedish Speech Analyzer for Language Learning Games: A Hybrid AI Approach to Language Assessment
Abstract
AbstractThis paper presents an automatic speech assessment system designed for Swedish language learners. We introduce a novel hybrid approach that integrates Microsoft Azure speech services with open-source Large Language Models (LLMs). Our system is implemented as a web-based application that provides real-time quick assessment with a game-like experience. Through testing against COREFL English corpus data and Swedish L2 speech data, our system demonstrates effectiveness in distinguishing different language proficiencies, closely aligning with CEFR levels. This ongoing work addresses the gap in current low-resource language assessment technologies with a pilot system developed for automated speech analysis.
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Interdisciplinary Bridge
— Deep Learning and Interdisciplinary and Machine Learning and Natural Language Processing and Speech & Audio
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Authors
Topics
Machine Learning > Application Areas > Domain Adaptation
Natural Language Processing > Applications > Machine Translation
Natural Language Processing > Applications > Text Classification
Speech & Audio > Recognition > Automatic Speech Recognition
Speech & Audio > Recognition > Speech Recognition
Speech & Audio > Analysis > Speech Enhancement
Speech & Audio > Analysis > Speech Analysis
Deep Learning > Models > Large Language Models
Interdisciplinary > Education