From Emotion To Empathy: Bringing Human Experience To Voice AI

The last few years have seen increased adoption of voice technology, with the usage of voice assistants booming across the globe. A lot of it has to do with advancements in speech recognition technology, easy accessibility to voice interfaces and availability at the right time and the right place. Not only that, but Covid-19 has acted as a catalyst for businesses.

Popularly referred to as the “fourth channel of sales,” voice technology is impacting how consumers interact with brands, preferring the immediacy and interpersonality of phone calls. Voice assistants are not only helping people get through their regular routines; they have become essential for businesses hoping to assist customers, improve employee engagement, enhance communication efficiencies and elevate user experiences.

While voice is emerging as a prominent channel of communication, the focus now is on making it more humanized. In 2021, Forrester predicted that “voice will be the channel for service as empathy takes center stage.” That’s because, powered by advanced NLP, voice assistants are capable of delivering natural conversational experiences that reduce the “robotic” feel users typically dislike. Voice assistants will only become more mainstream if synthetic monotones are completely replaced by conversational human tones. And conversational AI is key to achieving this feat.

Humanized Voice Interactions With Conversational AI

In today’s reality, a voice AI agent that understands the semantics of language, dialects, emotions, lilt and figures of speech is not merely a figment of imagination in sci-fi films anymore. Developments in conversational AI are enabling voice tech to deliver more accuracy in intent discovery. Next-gen voice AI agents are now able to start, pause, listen and stop during a conversation. For instance, if an AI agent asks a customer, “Hi, Phil! Can you please tell me what’s wrong with your food order?” the customer will relay his story in very natural language. In such cases, the AI agent will have the ability to understand when the customer’s response is complete before it starts responding.

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