If you don’t know what NLP is, the acronym stands for natural language processing (NLP). It’s a discipline within artificial intelligence and machine learning that allows machines to read human languages and unearth insights or meanings out of them and take action. Alexa, the Amazon voice service, is an example of a solution based on NLP.
Natural language processing has the ability to take unstructured data gathered from conversations, social media, and emails and find meaning in it. It can pick up on subtext as well, including sarcasm and irony. The technology is used to advance a variety of industries such as healthcare, education, and the business world.
Here are some common NLP tasks being used in software programs today:
Hospitals and clinics are using NLP in the form of voice-activated assistants and speech recognition platforms to create better care for patients. The technology is capable of reducing wait times for patients, expanding access to patient information, cutting costs and delays, and improving the quality of patient information available.
Colorado-based UCHealth developed a smart assistant called Livi that provides custom support to patients based on their unique needs. The tool links up with UCHealth and helps in providing test results to patients, as well as paving the way for managing appointments and creating secure messaging with physicians.
NLP is also being used to improve learning in the classroom. The technology has the capability to help out students with applications such as The Writing Mentor developed by Google Docs. The Google add-on provides students with feedback on their writing such as topic development, coherence, word choice, and other elements.
A customer calls in to a contact center. An automated voice responds asking the reason for a call. “I have a question about my account” or “I have an issue with your product,” the customer answers.
The NLP system behind the voice understands what the customer is saying and routes the call to the appropriate human customer service agent. The customer is able to communicate in conversational language and get a fast response, making the customer happy.
Companies can earn more money with NLP by leveraging technology for marketing goals. One way to do so is by creating chatbots that pop up whenever consumers visit their website. The bot would then gather information about these visitors and use that information to send targeted ads and content their way.
NLP is also a useful marketing tool in understanding the language of social media and the sentiment behind it. With NLP, businesses can gain insights from text and emoticons about their marketing campaigns as well as the consumer sentiment about their brand, products, and services. They can quickly assess what the public thinks about them and use that information to make informed decisions on how to move forward.
Many business decisions are based on sentiments influenced by the news, for example, with financial services and what’s happening in the stock market. Natural language processing can extract and analyze news content presented in the form of text, infographics, and images and provide summaries for decision-making.
NLP is commonly used in email filtering for identifying recipients, detecting spam, and automatically routing emails to appropriate folders or individuals. And it can be employed in document processing. For example, NLP is combined with Robotic Process Automation (RPA) in the Automation Anywhere IQ Bot to automatically classify, extract, and validate information from business documents and emails. It can help accelerate and streamline the task that traditionally has been time- and labor- intensive for human workers. In addition, NLP is being incorporated into everyday work tools such as spell checkers and auto-correct applications.
These are just some of the NLP applications, and the technology continues to evolve, opening the door for new applications and industries.
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