AIMC Topic: Language

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Multi-granularity heterogeneous graph attention networks for extractive document summarization.

Neural networks : the official journal of the International Neural Network Society
Extractive document summarization is a fundamental task in natural language processing (NLP). Recently, several Graph Neural Networks (GNNs) are proposed for this task. However, most existing GNN-based models can neither effectively encode semantic n...

Public Discourse and Sentiment Toward Dementia on Chinese Social Media: Machine Learning Analysis of Weibo Posts.

Journal of medical Internet research
BACKGROUND: Dementia is a global public health priority due to rapid growth of the aging population. As China has the world's largest population with dementia, this debilitating disease has created tremendous challenges for older adults, family careg...

Artificial intelligence for topic modelling in Hindu philosophy: Mapping themes between the Upanishads and the Bhagavad Gita.

PloS one
The Upanishads are known as one of the oldest philosophical texts in the world that form the foundation of Hindu philosophy. The Bhagavad Gita is the core text of Hindu philosophy and is known as a text that summarises the key philosophies of the Upa...

Synthesizing theories of human language with Bayesian program induction.

Nature communications
Automated, data-driven construction and evaluation of scientific models and theories is a long-standing challenge in artificial intelligence. We present a framework for algorithmically synthesizing models of a basic part of human language: morpho-pho...

A Bi-level representation learning model for medical visual question answering.

Journal of biomedical informatics
Medical Visual Question Answering (VQA) targets at answering questions related to given medical images and it contains tremendous potential in healthcare services. However, researches on medical VQA are still facing challenges, particularly on how to...

Eliminating Data Duplication in CQA Platforms Using Deep Neural Model.

Computational intelligence and neuroscience
Primary research to detect duplicate question pairs within community-based question answering systems is based on datasets made of English questions only. This research put forward a solution to the problem of duplicate question detection by matching...

Regional Language Speech Recognition from Bone-Conducted Speech Signals through Different Deep Learning Architectures.

Computational intelligence and neuroscience
Bone-conducted microphone (BCM) senses vibrations from bones in the skull during speech to electrical audio signal. When transmitting speech signals, bone-conduction microphones (BCMs) capture speech signals based on the vibrations of the speaker's s...

Sentiment Analysis and Emotion Recognition from Speech Using Universal Speech Representations.

Sensors (Basel, Switzerland)
The study of understanding sentiment and emotion in speech is a challenging task in human multimodal language. However, in certain cases, such as telephone calls, only audio data can be obtained. In this study, we independently evaluated sentiment an...

Analysis of Cross-Cultural Communication in English Subjects and the Realization of Deep Learning Teaching.

Computational intelligence and neuroscience
In subject teaching, subject characteristics are the logical starting point for teaching development, and a deep understanding of subject characteristics is the basis for effective teaching. In practice, due to ignoring the cross-cultural understandi...

Bi-directional long short term memory-gated recurrent unit model for Amharic next word prediction.

PloS one
The next word prediction is useful for the users and helps them to write more accurately and quickly. Next word prediction is vital for the Amharic Language since different characters can be written by pressing the same consonants along with differen...