Quick Concepts: Natural Language Processing
What is Natural Language Processing?
Natural language processing (NLP) is a branch of artificial intelligence that enables machines to receive, analyze, and produce language in a way similar to that of humans. It can be used to process text or speech, in documents and recordings as well as live conversations. NLP allows humans to interact with machines in a direct and natural way.
How does NLP work?
NLP has multiple components, including speech or text recognition, natural language understanding, and natural language generation. These components are further broken down into numerous subtasks that are performed using specialized algorithms. A few examples of these tasks are:
- Optical character recognition (OCR) – extracting meaningful language from images of text
- Speech segmentation – taking a chunk of speech and correctly dividing it into words (this is a complex task due to variations in accents, speaking styles, and voices)
- Morphological segmentation – understanding grammar and meaning by examining word segments and structures (tenses, prefixes, suffixes, etc.)
- Named entity recognition (NER) – extracting important information such as names, places, organizations, dates, numbers, and email addresses from text
- Word sense disambiguation – looking at words that have multiple meanings and determining which meaning is applicable in the given context
- Sentiment analysis – extracting subjective information about opinions and emotions and classifying them as positive, negative, or neutral
What are the uses and benefits of NLP?
NLP is capable of high-level actions such as translating between languages, summarizing texts, generating stories, converting verbal descriptions into images or models, correcting grammar, and answering questions. NLP enhances accuracy and efficiency in documentation (such as medical record classification and analysis), improves customer support through chatbots, enables large-scale sentiment analysis, and can extract key information from large volumes of text quickly and effectively. Widely used applications of NLP include online search engines, spam detection, predictive text and autocorrect, virtual assistants and chatbots, speech-to-text and text-to-speech services, and language translation. Though we may not be aware of it, NLP has become a mainstay of everyday technology.
Accelerate AI with Annotated Data
Check Out this Article on Why Your Model Performance Problems Are Likely in the Data
follow us