With natural language processing, your chatbots can be made to feel more human and help your customers get the information they need quickly, enhancing customer experience.
Incorporate NLP systems to recognize voice commands, and elevate customer interactions with your service and brand to a higher level. Although NLP is based on text, a ‘voice system’ uses speech recognition to turn recognized speech into text and then performs further analysis of this text based on NLP. Speech recognition and NLP are often used together, for example, in Siri and Google Assistant.
Want to know whether tweets about your company are good or bad so that you can address your customers’ concerns? Sentiment analysis uses NLP to help businesses understand what’s being said about them on the web and social media.
Fighting spam and organizing inboxes
Spam detection uses Natural Language Processing to keep unwanted emails and other messages out of your inbox. NLP can also be used to sort messages from certain contacts into separate folders.
If you want to build a translation feature into your application, you’ll need Natural Language Processing. The challenging part of machine translation is not translating individual words but preserving meaning. This is a complex technical issue that’s right at the heart of NLP.
Advanced “conversational” search
Website users are human, and, like all humans, they sometimes forget some details, make spelling errors, confuse brands, or use slang or “conversational” language when running searches. NLP takes into account all these things, connects the dots, and provides accurate results that are both relevant and valuable to the customer.
Natural Language Processing can automatically summarize long documents or extract relevant keywords for searching. The legal industry makes use of these types of NLP applications, for example, to help lawyers sort through thousands of pages of documents in legal cases to find relevant information.