Academic Articles & Research Papers

Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition

This book takes an empirical approach to language processing, based on applying statistical and other machine-learning algorithms to large corpora.Methodology boxes are included in each chapter. Each chapter is built around one or more work...

Label-Guided Data Augmentation for Chinese Named Entity Recognition

Chinese named entity recognition (NER) is a fundamental natural language processing (NLP) task that involves identifying and categorizing entities in text. It plays a crucial role in applications such as information extraction, machine tran...

Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing

Pretraining large neural language models, such as BERT, has led to impressive gains on many natural language processing (NLP) tasks. However, most pretraining efforts focus on general domain corpora, such as newswire and Web. A prevailing a...

Stanza: A Python Natural Language Processing Toolkit for Many Human Languages

We introduce Sta n z a , an open-source Python natural language processing toolkit supporting 66 human languages.Compared to existing widely used toolkits, Sta n z a features a language-agnostic fully neural pipeline for text analysis, incl...

Natural Language Processing

Natural language processing is widely discussed and researched topic nowadays.As it is one of the oldest areas of research in machine leaning it is used in major fields such as machine translation speech recognition and text processing.Natu...

Large Language Models in Healthcare and Medical Domain: A Review

The deployment of large language models (LLMs) within the healthcare sector has sparked both enthusiasm and apprehension. These models exhibit the remarkable ability to provide proficient responses to free-text queries, demonstrating a nuan...

Weighted DAG Automata for Semantic Graphs

Graphs have a variety of uses in natural language processing, particularly as representations of linguistic meaning. A deficit in this area of research is a formal framework for creating, combining, and using models involving graphs that pa...

Natural Language Processing

Natural language processing is a fast-evolving field with popular applications in language translation, speech recognition, text classification, and summarization of text, among others. The central aspect of NLP is vectorizing text data. Te...

Natural Language Processing

Natural Language Processing

Natural language processing (NLP) is an interdisciplinary subfield, which has components from major fields such as linguistics, computer science, and artificial intelligence. NLP is mainly concerned with the interaction between humans and c...

Paradigm Shift in Natural Language Processing

Abstract In the era of deep learning, modeling for most natural language processing (NLP) tasks has converged into several mainstream paradigms. For example, we usually adopt the sequence labeling paradigm to solve a bundle of tasks such as...

Natural language processing

This chapter introduces key natural language processing concepts and terminology. The ultimate objective of natural language processing is to allow people to communicate with computers in much the same way they communicate with each other. ...

Context-Aware Bidirectional Neural Model for Sindhi Named Entity Recognition

Named entity recognition (NER) is a fundamental task in many natural language processing (NLP) applications, such as text summarization and semantic information retrieval. Recently, deep neural networks (NNs) with the attention mechanism yi...

What Is Natural Language Processing?

Deep learning and machine learning continues to proliferate throughout various industries, and has revolutionized the topic that I wish to discuss in this book: natural language processing (NLP). NLP is a subfield of computer science that i...

Natural Language Processing

This chapter uncovers some of the basic techniques to tackle text data using PySpark. Today's textual form of data is being generated at a lightning pace with multiple social media platforms offering users the options to share their opinion...

Pathways to schizophrenia: Divergent effects of childhood trauma and polygenic risk on cognition and subcortical dynamics.

Application of 3D-Slicer combined with 3D printing technology in training neurosurgery resident physicians' imaging spatial cognition and clinical reasoning: A self-controlled before- and after-study.

Natural Language Processing Advancements By Deep Learning: A Survey

Natural Language Processing (NLP) helps empower intelligent machines by enhancing a better understanding of the human language for linguistic-based human-computer communication. Recent developments in computational power and the advent of l...

An Introduction Natural Language Processing

The study of the way native human dialects and computer systems interact is known as natural language processing.Cognitive languages require the use of NLP, which has connections to artificial intelligence and computer engineering.In artifi...

A Model-Driven Approach Employing DSL and Generation Templates to Accelerate the Development of Conversational Agents for Smart Tourism

Conversational agents are intelligent, ubiquitous software applications widely used across various sectors, such as commerce, tourism, and more. Their key benefits include automating tasks, improving customer service, and ensuring service a...