Voice AI still has major hurdles before it reaches a breakout moment comparable to ChatGPT, according to executives from PolyAI and Otter speaking at the HumanX conference, as cited by TechCrunch. PolyAI CTO Shawn Wen said that even though full-duplex models have already been developed, the sector has not yet reached its defining turning point. In his view, the next technical hurdle is making inference fast enough for conversations to feel natural rather than delayed or mechanical.
Otter CMO Alex Gay pointed to a different but related set of requirements for automation. He said speaker identification, intent capture, and the ability to combine those signals with organizational knowledge are key steps in building useful voice-based systems. He also stressed that generated speech needs to carry the same emotional expression people expect in a real human conversation. Without that, he said, the product remains little more than a question-and-answer bot. Both executives agreed that current voice AI systems still need improvement in understanding users and in transcription accuracy.
Voice AI has yet to reach its own ChatGPT moment, even though full-duplex models already exist, PolyAI CTO Shawn Wen said at the HumanX conference, according to TechCrunch.
Wen said the next challenge is to make inference fast enough for conversations to feel natural.
Understanding and expression remain open problems
Otter CMO Alex Gay said speaker identification, intent capture, and combining those capabilities with organizational knowledge are key steps toward automation.
He added that spoken output must convey the same emotional expression people get in a real conversation with another person. Otherwise, it is still just a question-and-answer bot.
Both executives said current voice AI systems still need work in user understanding and transcription accuracy.
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