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Digital Themes

Natural Language Processing

What is Natural Language Processing?

Natural Language Processing (NLP) is a category of artificial intelligence (AI) that enables computers to understand, translate, and manipulate human language. NLP relies on computer science and computational linguistics attempting to fully rationalize human communication for computer understanding.

NLP technology has recently been progressing due to the accessibility of big data, increasing computing power, and improved algorithms combined with a renewed interest in human-to-machine conversations. Humans speak and write in English, French, or any number of foreign languages that can be learned and translated, but a computer’s native language (i.e. machine language) is untranslatable to most people. Human languages are extremely diverse and full of semantical complexities in both textual and verbal communications. Each language has its own unique dialects, accents, grammar, and slang, and in writing, misspelled or abbreviated words are quite normal.

Natural language processing involves various statistical and machine learning techniques, as well as algorithmic and rules-based methods, as different approaches are required for the various text-based and voice-based data applications. NLP tasks, such as part-of-speech tagging, can reduce language into smaller, elemental pieces attempting to recognize the relationships between various pieces.

An example of NLP technology in action is voice-activated smart devices. Computers are now able to activate upon "hearing" a human voice, understand what is being said or asked, carry out a task, and then provide an answer or confirmation in the user's chosen language. NLP enables computers to converse with humans in their personal languages and even read a piece of text, hear human speech, interpret that text or speech, measure user sentiment, and assess which parts of the text or speech are valuable data. NLP functionality allows computers to analyze language-based, unstructured data consistently. From social media posts to legal files and medical records, automating unstructured data is a crucial step towards fully analyzing text and speech data in an efficient and unbiased way.

What are the business benefits of Natural Language Processing?

  •  Text analytics, a technique of advanced NLP, can identify trends from customer feedback emails, surveys, and call center communications to extract the main cause of any customer dissatisfaction and help to resolve issues.

  • Unstructured data, such as open-ended survey responses, often provide the most actionable insights, but searching through it all is a laborious process. NLP tools, such as machine translation and AI-based tools, allow you to assign value to various responses and access those invaluable insights.

  • NLP tools can automate processes and reduce costs by employing 24/7 automated data collection and analytics systems. This not only reduces the number of staff you'll require but can also monitor customer feedback and ticket routing.

  • NLP tools provide you with a better understanding of your market, by understanding the language of your customer base and how to better interact with them.

  • NLP offers the ability to complete large-scale text analysis by extracting information from numerous documents, emails, social media posts, and search engine reviews in minutes. Manually, this could take weeks.
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