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Voice AI & Technology

Natural Language Processing (NLP)

Natural language processing (NLP) is the field of artificial intelligence that enables computers to read, interpret and produce human language, in written or spoken form.

Definition

Natural language processing brings together methods that let software work with human language. Classic tasks include splitting text into words, recognising names of people and places, classifying a message by topic, detecting the language, translating, and extracting key information from documents. Chatbots, search engines, spam filters and voice assistants all rely on it.

For years NLP depended on hand-written rules and then on statistical models trained for one task at a time. Today large language models handle many of those tasks at once. Performance is measured task by task, for example the share of messages classified correctly, and it is checked against examples labelled by people, ideally taken from your own context.

NLP is only as good as the language it has seen. Slang, regional expressions, mixed languages, irony and short answers are harder, and results are usually weaker in languages with less training data. Before relying on it, test it on real examples in every language you use and keep people able to read the original text.

Key points

  • It covers reading, interpreting and producing human language.
  • Typical tasks: classification, entity extraction, translation, summarisation and language detection.
  • Large language models now perform many NLP tasks with one model.
  • Accuracy is measured against examples labelled by people.
  • Test on your own languages, slang and regional expressions before relying on results.

Example

An HR team receives 400 free-text answers to an annual survey. An NLP tool groups the comments by topic, such as workload, management and pay, and flags the topics that appear most. A person then reads a sample of each group to confirm that the grouping makes sense.

Frequently asked questions

What is the difference between NLP and an LLM?

NLP is the whole field of working with language by computer. An LLM is one recent and powerful type of model used for many NLP tasks.

Does NLP work in every language?

Not equally well. Widely spoken languages have more data and tools, while smaller languages and dialects can give weaker results.

Is NLP used in HR?

Yes, for example to analyse survey comments, sort messages or summarise conversations. The output should help people read faster, not replace their judgement.

Related terms

Large Language Model (LLM)A large language model (LLM) is an AI model trained on very large amounts of text to predict and generate language, which lets it answer questions, summarise, translate and hold a conversation.Sentiment AnalysisSentiment analysis is the use of language processing to detect whether a text or a spoken comment expresses a positive, negative or neutral opinion, and sometimes the emotion or intensity behind it.Speech-to-TextSpeech-to-text, also called automatic speech recognition, is the technology that converts spoken audio into written text so that software and people can search, analyse and act on what was said.Conversational AIConversational AI is software that lets people interact with a computer through natural spoken or written dialogue, understanding what they mean and replying in a way that fits the conversation.

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What is Natural Language Processing (NLP)? Definition and examples | Passisto