The next phase of voice technology is natural language understanding (NLU), which uses AI, machine learning and data science to place vocal cues in the context of people’s lives.
Today’s voice apps like Alexa and Siri respond to basic vocal cues via natural language processing (NLP). They can do amazing things, but only in a narrow range of scenarios. For instance, a voice assistant can let you use a smartphone to tell your car to warm itself up on a cold winter morning so you can enjoy a toasty drive to work.
It’s handy, but not necessarily essential.
Soon, NLU will take things to the next level — syncing your voice commands with your calendar, travel habits, entertainment preferences and local weather. If you’re going out of town on business today, your voice assistant will guide you to the right gate at the airport and make sure you know about the blizzard that’s rolling in.
When your voice assistant starts taking a lot of the friction out of your life, it starts feeling more essential every day.
Organizations getting up to speed with NLP must prepare for the evolution of NLU. After all, NLU will enable companies to personalize their customer interactions to create unforgettable experiences that can seal brand loyalty for years. If you miss that chance, you might not get it back.
If you’re already collecting voice information via call centers, customer feedback and other venues, you’ve got a nice head start on NLU. All those digitized calls form a data foundation that helps reveal why people interact with your organization. NLU technologies can scan those voice files and correlate them with people’s actions to develop models of human intent.
At DMI, we’re developing hybrid systems that will use APIs, microservices and other technologies to help organizations take advantage of the evolution of natural language understanding. It is an evolution we are leading with a concise methodology to implementing next-generation voice technology.