AIMC Topic: Language

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Diversity Learning Based on Multi-Latent Space for Medical Image Visual Question Generation.

Sensors (Basel, Switzerland)
Auxiliary clinical diagnosis has been researched to solve unevenly and insufficiently distributed clinical resources. However, auxiliary diagnosis is still dominated by human physicians, and how to make intelligent systems more involved in the diagno...

A Chinese verb semantic feature dataset (CVFD).

Behavior research methods
Language is an advanced cognitive function of humans, and verbs play a crucial role in language. To understand how the human brain represents verbs, it is critical to analyze what knowledge humans have about verbs. Thus, several verb feature datasets...

A Lightweight Sentiment Analysis Framework for a Micro-Intelligent Terminal.

Sensors (Basel, Switzerland)
Sentiment analysis aims to mine polarity features in the text, which can empower intelligent terminals to recognize opinions and further enhance interaction capabilities with customers. Considerable progress has been made using recurrent neural netwo...

TopicBERT: A Topic-Enhanced Neural Language Model Fine-Tuned for Sentiment Classification.

IEEE transactions on neural networks and learning systems
Sentiment classification is a form of data analytics where people's feelings and attitudes toward a topic are mined from data. This tantalizing power to "predict the zeitgeist" means that sentiment classification has long attracted interest, but with...

Negation-based transfer learning for improving biomedical Named Entity Recognition and Relation Extraction.

Journal of biomedical informatics
BACKGROUND AND OBJECTIVES: Named Entity Recognition (NER) and Relation Extraction (RE) are two of the most studied tasks in biomedical Natural Language Processing (NLP). The detection of specific terms and entities and the relationships between them ...

Multimodal Data Matters: Language Model Pre-Training Over Structured and Unstructured Electronic Health Records.

IEEE journal of biomedical and health informatics
As two important textual modalities in electronic health records (EHR), both structured data (clinical codes) and unstructured data (clinical narratives) have recently been increasingly applied to the healthcare domain. Most existing EHR-oriented stu...

NCSP-PLM: An ensemble learning framework for predicting non-classical secreted proteins based on protein language models and deep learning.

Mathematical biosciences and engineering : MBE
Non-classical secreted proteins (NCSPs) refer to a group of proteins that are located in the extracellular environment despite the absence of signal peptides and motifs. They usually play different roles in intercellular communication. Therefore, the...

Deep learning reveals what vocal bursts express in different cultures.

Nature human behaviour
Human social life is rich with sighs, chuckles, shrieks and other emotional vocalizations, called 'vocal bursts'. Nevertheless, the meaning of vocal bursts across cultures is only beginning to be understood. Here, we combined large-scale experimental...

Detecting Lombard Speech Using Deep Learning Approach.

Sensors (Basel, Switzerland)
Robust Lombard speech-in-noise detecting is challenging. This study proposes a strategy to detect Lombard speech using a machine learning approach for applications such as public address systems that work in near real time. The paper starts with the ...

Towards a simultaneously speaking bilingual robot: Primary study on the effect of gender and pitch of the robot's voice.

PloS one
With fast and reliable international transportation, more people with different language backgrounds can interact now. As a result, the need for communicative agents fluent in several languages to assist those people is highlighted. The high cost of ...