"Hey Siri"

When you call for Alexa or Siri, how do you think each robot is able to think of and respond to your message? NLP is the answer to how these robots are able to elicit a response. Specifically NLP stands for Natural Language Processing. It's used to bridge the gap between human language and machine processing. An important part of human language is tone, and is a difficult element for machines to capture. Sentiment analysis helps identify the tone of text converted. If a customer submits a certain feedback or response on the product, the company would not individually go through every response being made. They use sentiment analysis models to sense the tone of every message being sent and return the data as a positive, negative, or neutral response. These condensed forms of data can then be analyzed by the company more efficiently. NLP is useful for more than just voice recognition and speech-to-text conversion. Emails can be filtered as spam through the recognition of some phrases in the email that make it seem like a marketing ploy.





How does NLP recognize these phrases? A useful tool is the n-gram model. This technique breaks down the message in different word lengths. N-gram models help to straighten out text that is diluted by excessive background noise by guessing the words that come after an unclear verse. For example, “minutes” and “minuets” sounds very similar, however “minuets” would not work in most contexts, and the n-gram replaces the word that fits with the context of the sentence. Chatbots also use AI to help customers obtain the information they need without another person to regulate the conversation. They try to replicate human conversation as much as possible. They save businesses time and money, and are a crucial (and more widely-known) part of NLP.


Products that use NLP are Siri, Alexa, Google Home, and Cortana. Another software that uses NLP is Grammarly. Beyond auto-corrections and spelling mistakes, Grammarly helps condense and improve the grammar of a given text. NLP is used to detect language that can be improved by checking for specific phrases that are hard coded or run through algorithms. Google translate is another great example of NLP. The Google translate software is able to translate over 101 languages. It is able to convert jargon, idioms, figurative language, and other highly specific features in other languages and convert them.


In conclusion NLP can act as a powerful tool that connects the diversity and complexity of human communication to machine language.


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