Currently, Natural Language Processing has made a big difference in many companies that have opted for a heavier technology presence.
This article aims to teach the use cases of the most significant NLP for various industries.
Let us begin!
According to the article AIMultiple, these are the main uses of Natural Language Processing:
The first NLP-based translation machine was introduced in the 1950s by Georgetown and IBM. This was capable of automatically translating 60 sentences from Russian to English.
Translation applications today leverage NLP and machine learning to understand and produce accurate translation of global languages in text and speech formats.
It is used to identify a misspelled word by comparing it with a set of relevant words in the dictionary of the language used as the training set.
The misspelled word is then sent to a machine learning algorithm that calculates the distance of the word from the correct words in the training set, adds, removes, or replaces letters in the word.
Combines NLP with certain machine learning algorithms (for example, supervised learning, recurrent neural networks (RNN), or latent semantic analysis (LSA)). This is in order to predict the probability that a following word or sentence completes the meaning.
4. Conversational AI Conversational
AI is the technology that enables automatic conversation between computers and humans. In simple words, it is the heart of chatbots and virtual assistants like Siri or Alexa.
Conversational AI applications rely on NLP and intent recognition to understand user queries, drill down into their training data, and generate a relevant response.
5. Automated speech/speechSpeech
Recognition, also known as automatic speech recognition (ASR) and speech-to-text (STT), is a type of software that converts human speech from its analog form (acoustic sound waves) into a digital form that can be recognized by machines.
Today, smartphones integrate voice recognition with their systems to perform voice searches (for example, Siri) or provide more accessibility to text messages.
Finally, Natural Language Processing is a technological technique that has a wide range of uses. This has favored a large number of companies and has made them more efficient and competitive.
Taking advantage of the technological wave and all the benefits that we can extract from it, at LISA insurtech we have acquired knowledge in NLP in order to offer the insurance industry the ability to operate effectively.
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In our next article, we will be breaking down how NLP is applied in insurance and cybersecurity