Balto has released its next generation of intent-based conversational dialogue models in its real-time guidance platform for contact centers.
Using deep learning techniques, Balto’s conversational dialogue modeling provides artificial intelligence-powered real-time guidance during calls. With the latest generation of intent-based language processing, Balto’s proprietary AI library and Smart Checklist are now even smarter, recognizing the true intention of the speaker and allowing for more natural conversation while maintaining script integrity.
The intent-based language processing enhancements augment the real-time guidance platform by relying less on specific keywords. Going beyond the AI’s ability to hear trigger words that would then prompt a subtle nudge to agents during calls, the new model identifies and decodes synonyms, rephrasing, paraphrasing, substitutions, and common idiomatic expressions.
“Before we were decoding in a very syntactically based way, looking for pattern matches. That works really well in a lot of use cases. If you have a very strict standard, that’s OK. But that can be restrictive to agents,” said Mike Goldstein, vice president of engineering at Balto, in a statement. “Our next generation of intent-based natural language processing allows agents to be more natural in their conversations and still hit script marks.”
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