1 Jul 2022| Digital Marketing Strategies & ORM
Emerging Natural Language Processing Technologies Of 2022
Natural Language Processing is currently one of the most popular subjects in data science. This field study is costing companies a lot of money. Everyone is attempting to grasp Natural Language Processing and its applications to pursue a profession in this field. Every business wants to incorporate technology in some way into its operations. Do you have any idea why?
Because natural language processing has evolved into something so intense and profound in such a short period that no one could have predicted. We need to look at its applications to comprehend the strength of natural language processing and how it affects our lives. As a result, I’ve compiled a top-ten list of natural language processing applications.
Let us begin with the most basic application of natural language processing.
Grammar checking is one of the most well-known applications of natural language processing. Grammar checkers identify and repair grammatical problems in writing. They are helpful in language learning, text production, and various other situations.
While we can still manually examine our error (to double-check), a grammar checker would be more effective and faster in detecting severe grammatical problems and misspellings and making appropriate correction suggestions.
Grammarly, WhiteSmoke, and ProWritingAid are examples of writing programs that employ NLP to correct grammar and spelling problems. Grammarly focuses on a specific application of natural language processing (NLP) for grammatical assistance.
Grammar checkers have continued to add additional capabilities, and Grammarly, for example, allows you to check for plagiarism. Apart from grammatical aid, these programs also contain the text’s intelligibility and offer better synonyms. With these tools, you may improve the readability of your messages and effectively communicate your point.
When you type 2-3 letters into Google to search for something, it displays a list of probable search keywords. Alternatively, if you search for something with typos, it corrects them while still returning relevant results. Isn’t it incredible?
It’s something that everyone utilizes regularly but rarely thinks about. It’s a fantastic illustration of how natural language processing is touching millions of people worldwide, including you and me. Both searches autocomplete and autocorrect, assist us in quickly discovering accurate results. Other companies, such as Facebook and Quora, have begun to use this feature on their websites.
Language models are the main force behind search-auto-complete and auto-correct.
Chatbots are artificial intelligence (AI) programs intended to interact with humans to make them sound human. Depending on their complexity, chatbots can either respond to specific phrases or carry on whole conversations, making it difficult to tell them apart from humans.
Natural Language Processing and Machine Learning are used to develop chatbots, which means they can comprehend the nuances of the English language and determine the true meaning of a text and learn from their interactions with humans and improve over time. Chatbots operates in two steps. They begin by defining the purpose of the question and gathering all data from the user that may be required to answer the query. Then they respond appropriately to the inquiry.
Machine translation systems have replaced traditional rule-based and dictionary-based language translators. The majority of machine language tools available now can translate millions of words from one language into a target language, which would have been extremely difficult to do manually in the past.
Businesses and individuals use language translation technologies to break down language barriers and interact with others who speak different languages in today’s globalized society. This is achievable thanks to the development of powerful machines, data availability, and neural network evolution.
Have you ever used Google Translate to look up the definition of a word or phrase in another language? Yes, it’s true! And isn’t it wonderful how quickly it can translate a piece of text from one language to another? Machine Translation is the method behind it.
Machine Translation is the process of automatically translating text from one language to another while maintaining its meaning.
Machine translation systems used to be dictionary- and rule-based, and they were only somewhat successful. Machine translation has become entirely accurate in transforming text from one language to another, thanks to advancements in the science of neural networks, the availability of massive data, and powerful processors.
Today, applications like Google Translate make it simple to transform text between languages. Many people and businesses use these techniques to overcome language barriers and achieve success.
Many well-known corporations place large bets on CUI ( Conversational user interface). The term “computer user interface” (CUI) refers to user interfaces for computers that can replicate discussions with real people. Interactive systems are another widespread and promising use.
Apple’s Siri, Microsoft’s Cortana, Google’s Google Assistant, Amazon’s Alexa, and others are the most common CUIs in our daily lives.
CUIs can also be incorporated into automobiles, particularly electric ones (electric vehicles). In 2018, NIO, an electric vehicle manufacturer focused on design and development, released its own set of CUI called NOMI. CUIs in cars can function similarly to Siri in terms of appearance. Drivers can concentrate on steering while requesting the CUI to modify the A/C temperature, play a song, lock windows/doors, and route them to the nearest gas station, among other things.
People increasingly use social media to express their opinions about a product, policy, or issue. These may offer helpful information about a person’s preferences and dislikes. As a result, studying this unstructured data can lead to valuable insights. Natural Language Processing comes to the rescue once more.
Companies utilize various NLP techniques to evaluate social media posts and learn what their customers think about their products. Companies also use social media monitoring to learn about the issues and problems that their customers are encountering due to using their products. The government and businesses use it to identify potential dangers to national security.
These are the most common Natural Language Processing applications, and chances are you’ve never heard of them! You may have come across Natural Language Processing before but had no idea what it was. However, you are now aware of the vast array of applications for this technology and its benefits in our daily lives. NLP is also employed in various applications, including social media monitoring, translation tools, smart home devices, survey analytics, and more. Several online courses are available if you wish to learn more about this technology.
To know more about NLP and various technologies, contact the ONPASSIVE team.
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