Natural language processing (NLP) is a form of artificial intelligence (AI) that allows humans to interact with computers using conversational speech. This requires the computer to recognize what is being said and, in turn, process commands and respond to the person.
NLP uses two primary methods to process speech: syntactic analysis and semantic analysis. Syntactic analysis applies rules about sentence structure (syntax) to derive part of the meaning of what's being said. Natural language processing supplements this with semantic analysis, which tries to distill the meaning of the words. Deep learning algorithms translate human language into a format the computer can use.
Although many improvements have been made to natural language processing , it's still not perfect. For example, it has difficulty detecting conversational nuances such as sarcasm. Additionally, speech habits like using slang, mumbling, or stuttering can trip it up.
Probably the most well known use of natural language processing is found in automated attendants like Apple's Siri and Amazon's Alexa. However, contact centers have also been on the forefront of using NLP to deliver very tangible business and customer experience benefits.
Interactive voice response (IVR) systems commonly use natural language processing to enable customers to interact with menus using natural speech, as well as facilitate self-service transactions. Additionally, speech analytics tools can comb through a multitude of interaction recordings to create transcripts, identify common call drivers, flag potential compliance issues, and more.
As natural language processing continues to mature and improve, it's likely that additional contact center applications will emerge.
