AIMC Topic: Language

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Simultaneous interpreting with auto-subtitling: Investigating viewer cognitive effort, stress, and comprehension.

PloS one
Simultaneous interpreting (SI) enables real-time cross-language communication without significant delays and is vital for fast-paced environments such as multilingual conferences. Automatic subtitles, powered by artificial intelligence (AI), is an im...

Navigating tenses in Bengali sentences: A stacked ensemble model for enhanced prediction.

PloS one
Tense classification in Bengali sentences is a fundamental yet unsolved problem of Bangla natural language processing (NLP) which is essential for tasks like machine translation, sentiment analysis, grammar correction, writing assistance and sentence...

Visual language transformer framework for multimodal dance performance evaluation and progression monitoring.

Scientific reports
Dance is often perceived as complex due to the need for coordinating multiple body movements and precisely aligning them with musical rhythm and content. Research in automatic dance performance assessment has the potential to enhance individuals' sen...

Efficient neural encoding as revealed by bilingualism.

Proceedings of the National Academy of Sciences of the United States of America
The remarkable human capacity for bilingual and multilingual acquisition raises fundamental questions about how the brain develops efficient systems for processing multiple languages. In this study, we used neural network models trained on natural sp...

University english teaching evaluation using artificial intelligence and data mining technology.

Scientific reports
This work intends to drive reform and innovation in English teaching evaluation and support personalized English instruction. It utilizes deep learning (DL) and artificial intelligence (AI)-driven data mining technology to explore a reliable and effi...

What social stratifications in bias blind spot can tell us about implicit social bias in both LLMs and humans.

Scientific reports
Large language models (LLMs) are the engines behind generative Artificial Intelligence (AI) applications, the most well-known being chatbots. As conversational agents, they-much like the humans on whose data they are trained-exhibit social bias. The ...

A simulated dataset for proactive robot task inference from streaming natural language dialogues.

Scientific data
This paper introduces a dataset designed to support research on proactive robots that infer human needs from natural language conversations. Unlike traditional human-robot interaction datasets focused on explicit commands, this dataset captures impli...

Current Landscape and Future Directions Regarding Generative Large Language Models in Stroke Care: Scoping Review.

JMIR medical informatics
BACKGROUND: Stroke has a major impact on global health, causing long-term disability and straining health care resources. Generative large language models (gLLMs) have emerged as promising tools to help address these challenges, but their application...

Classifying Patient Complaints Using Artificial Intelligence-Powered Large Language Models: Cross-Sectional Study.

Journal of medical Internet research
BACKGROUND: Patient complaints provide valuable insights into the performance of health care systems, highlighting potential risks not apparent to staff. Patient complaints can drive systemic changes that enhance patient safety. However, manual categ...

Transfer learning driven fake news detection and classification using large language models.

Scientific reports
Today, the problem of using social media to spread false information is not only widespread but also quite serious. The extensive dissemination of fake news, regardless of whether it is produced by human beings or computer programs, has a negative im...