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Natural language processing
Natural Language Processing (NLP) is a branch of artificial intelligence that focuses on enabling computers to process, analyse, understand, interpret, and generate human language. NLP encompasses a wide range of tasks including text analysis, text classification, language translation, and speech recognition.
NLP aims to bridge the gap between human communication and computer understanding, allowing machines to interact with and respond to human language in a way that is contextually relevant and meaningful, thereby enabling the development of applications that leverage human language and speech.
Why do you need to use NLP in your business
By utilising NLP, businesses can personalise customer interactions, improve product development based on customer feedback, optimise marketing strategies, automate customer service with chatbots, and extract actionable intelligence from vast amounts of textual data.
Application areas for NLP
There are various use case for NLP including:
- Text analytics: With text analytics, written content can be analysed to generate insights. Text analytics enables the classification of text from a sentiment perspective, the extraction of key words and phrases, and well as the extraction and recognition of entities such as people, places or things. A common use case for text analytics is generating insights from customer comments on social media. Text analytics is able to classify the sentiment or tone of the customer comment, as well as extract key words and phrases that can then be use to route the comment to the appropriate person internally.
- Text to speech and speech to text: Text to speech and speech to text enable the conversion from one form to another. A use for text to speech is the reading out loud of written documents for those that may be visually impaired or prefer to listen as opposed to reading. A use case for speech to text is adding transcription on video or audio, such as the recording of online calls.
- Text and speech translation: Translation enables the translation of text from one language to one or many languages. Speech translation uses speech to text together with text translation to enable translation of the spoken word. Use cases for these include translating business documents or emails from one language to another, or enabling communication between people speaking different languages.
- Language understanding: With language understanding, you can build understanding into apps and bots. The language understanding capabilities allow the algorithms to interpret the user’s intent in written text and extracts key information in the text. A key use case is conversational AI where self-service bots autonomously interact with customers. With language understanding integrated, these bots can understand the meaning and intent of customers questions and answers and simulate a human conversation.