Siri, Alexa, Google Search, and other systems that use NLP are some examples. Through its various products & services, NLP is likely to aid in comprehending, interpreting, and manipulating human language.
The three main categories of NLP solutions are statistical NLP, rule-based NLP, and hybrid NLP. Optical character recognition (OCR), auto coding, text analytics, interactive voice response (IVR), pattern and image recognition, classification and categorization, and speech analytics are just a few of the recognition, analytics, and operational technologies that are part of Natural Language Processing. In a number of industry verticals, including automotive, retail and consumer goods, high tech and electronics, government, banking, financial services, and insurance (BFSI), health care and life sciences, research and education, and media and entertainment.
Natural language processing is used for applications like information extraction, question answering, machine translation, and report generation. Natural Language Processing is a subfield of AI that gives computers the ability to comprehend spoken and written language similarly to humans. In order to enable natural and human-like interactions, NLP is a conversational AI that is frequently used to implement advanced scalable dialogue systems that identify users' voice or text patterns, forecast their intent and sentiment, and answer with an adaptive and automated script. To serve consumers by communicating with them in texts or words, conversational AI uses NLP coupled with conventional technologies such as voice assistants, chatbots, or interactive speech recognition systems.
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