Fast, accurate, responsive: every person who uses a smart device expects results that meet their needs in no time. Search algorithm developers tirelessly improve result accuracy. Smartphone companies constantly come out with new features that boost efficiency. Robot scientists encourage us to use advanced tools in our homes.
But when it comes to voice recognition technology like Apple’s Siri, consumer expectations face major disappointment. Try to hold a conversation with Siri and you’re bound to be met with the iPhone assistant’s confusion, “What was that?” or “I’m sorry, I didn’t catch what you said.”
Innovators in the space of virtual user experiences are enthusiastic about ongoing tech developments, but conversational AI has lagged behind. People need to be able to communicate verbally with machines in a future that’s growing more virtual with every passing day.
Building voice AI to understand what you really want
Popular voice technology apps like Siri and Amazon Echo use AI-fueled systems and protocols that quickly search software to generate responses to basic commands. Asking a smart speaker to set an alarm for a certain time or dim the lights in the kitchen is doable. Initiating a back-and-forth conversation that encourages relevance, resembles personal opinion and extends new suggestions is infinitely more complicated.
It’s hard to comprehend just how complex even the most basic human conversation is: we remember, we recognize context, we apply the same vocabulary words to mean something specific based on a previous sentence. The possibilities for human interchanges are complex, something that tech innovators have long realized but been unable to solve for, until now.
Dialogues between human and computer have been gradually improving since the global introduction of Siri in 2011. This is, in part, because the body of recorded voice data has grown exponentially, giving rudimentary search-and-grab systems more to choose from. But the whole point of conversational AI is to sustain interaction both ways, and voice AI programs must continuously learn how to better understand human requests. Over time, speech search is advancing to understand what an individual really wants. The next added step: understand what the individual doesn’t want.
Training conversational AI to remember context and apply negation during search queries
The field of AI is still trying to see if machine learning can adequately recognize human error. Every day, humans make mistakes. We leave out small details, forget useful facts and we misunderstand and misspeak. When conversing with newer voice technology apps, being able to change our minds and restore the flow of dialogue with new information is key. Having the technology to understand when we slightly change direction is essential.
A conversational search app, MeetKai, is leading the industry to create real and useful solutions to this problem. By building a proprietary voice technology software and voice search engine from the ground up, its developers trained a digital voice assistant, Kai, to deliver advanced conversation. It can comprehend negation on demand and remember the context of your queries, just like a human would, to give you accurate results when you say “show me another result” without restarting your query from zero.
This means that when someone performs a voice search using Kai, they can direct the search result to leave out unwanted options in a multi-turn conversation.
Here’s an example of what could happen:
A person says, “What’s a good Brad Pitt movie to watch?”
Kai conducts its search, replying with: “Here’s Fight Club, an award-winning movie starring Brad Pitt and Edward Norton.”
But maybe the person has already seen this one or doesn’t want an action film. They can tell Kai, “No, not an action film. How about another one?”
The app will then refine the search, maintaining the original context of the person wanting to watch a Brad Pitt movie. This time, Kai knows to recommend Brad Pitt movies that are not the same genre as its original suggestion.
This operation doesn’t apply to entertainment only. Voice search apps like Kai’s can remember an individual’s preferences and customize their search results, which opens a whole new realm of possibilities where AI can offer new solutions to real and virtual-world problems.
Personalization leads to more sophisticated human-machine solutions
With new steps toward smarter conversation, interactive AI opens up a world of possibilities for consumers and businesses. Behavioral learning of individual preferences gives people the chance to explore individualized human-to-machine experiences.
The more voice search evolves to resemble natural human communication, the age of virtual personal assistants may peak. If voice technology apps advance enough to provide impressively accurate results to each individual, requests will become more and more beneficial to each user.
Much like targeted search engine results, conversational voice platforms can offer solutions to each specific user instead of delivering the same generalized results to everyone. The more a person uses this evolving technology, the more closely their conversational AI assistant, or “Kai”, can produce answers that truly help them.
Beyond automatic answers and suggestions, this type of communication luxury is sure to fill in the gaps that previously divided connection between human and computerized potential. Voice AI apps now present the option for users to discover possibilities that matter to them, and to help push technology forward in ways we can all access.
This article was written in cooperation with DN News Desk