Natural language processing (NLP) is a subfield of computer science and AI using machine learning to enable computers to understand and communicate with human language.
NLP enables computers and digital devices to recognize, understand and generate text and speech by combining computational linguistics, the rule-based modeling of human language together with statistical modeling, machine learning and deep learning.
NLP research has helped enable the era of generative AI, from the communication skills of Large Language Models (LLMs) to the ability of image generation models to understand requests. NLP is already part of everyday life for many, powering search engines, prompting chatbots for customer service with spoken commands, voice-operated GPS systems and question-answering digital assistants on smartphones such as Amazon’s Alexa, Apple’s Siri and Microsoft’s Cortana.
NLP also plays a growing role in enterprise solutions that help streamline and automate business operations, increase employee productivity and simplify business processes.
As regards common NLP Tasks, optical character recognition, speech recognition, speech segmentation, text to speech, word segmentation, tokenization, lemmatization, morphological segmentation, part of speech tagging, stemming, grammar induction, parsing, lexical semantics, distributional semantics, named entity recognition, sentiment analysis, multimodal sentiment analysis and a host of others are important.
Natural Language Toolkit (NLTK) is a library for NLP to provide combination linguistic resources including text processing libraries and pre-trained models, which makes it ideal for both academic research and practical applications. Other libraries include spaCY designed for industrial and production-grade NLP applications. It focuses on speed, efficiency, and practical deployment. SpaCy has key features such as fast tokenization, named entity recognition, dependency parsing, support for multiple languages, information extraction, document processing and enterprise NLP.
Hugging Face Transformers is another library for Natural Language Processing which offers access to numerous pertaining language models and has support to transformer architectures, large pre-trained model repository, fine tuning capabilities, text generation and summarization, question answering and translation. Its strength is the foundation of many modern LLM workflows. Gensim, Sentence Transformers, Allen NLP, Stanford CoreNLP are other libraries for Natural Language Processing.
(Hamid Siddiqui)
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