Solving Voice AI Latency Could Herald an Entirely New Human-Computer Interaction
While large language models are dominating headlines, we're missing a piece of the puzzle: natural voice interaction.
There's been a lot of hype around artificial intelligence, but our daily interactions with technology remain largely confined to taps, swipes, and typing. And we're still spending a lot of time on our phones.
What's missing is ultra-low latency voice AI, a technology that could change how we interact with our devices and potentially reduce our screen time.
Conversational AI's real-world applications have so far been severely limited. Call center AI still sounds robotic, voice interactions feel rigid, and educational tech struggles to hold attention. It's also still far from commonplace across industries.
That's because current text-to-speech systems require full sentences to provide context and drive prosody, the patterns of stress and intonation in speech. This creates latency over 400 miulliseconds, significantly slower than the human response time of 150 milliseconds, making interactions feel unnatural. The models are also massive, often requiring significant resources just to run basic operations. This has led to a distorted marketplace where large players use inefficient architectures to plug gaps rather than solving core problems.
But recent innovations are now allowing us to generate speech word by word, similar to how humans speak. We don't always know the exact words we're going to say, but we have a sense of how it should sound and feel.
This approach allows for near real-time speech generation while maintaining naturalness. By processing speech incrementally, we can reduce latency to just 25 milliseconds, significantly faster than both conventional systems (400 milliseconds) and even human response time (150 milliseconds). The latest models are also significantly smaller, meaning businesses can integrate advanced voice technology at a fraction of the cost without massive infrastructure investments.
The impact of ultra-low latency voice AI extends way beyond traditional applications. In digital gaming, where current solutions are too slow for real-time character interactions, sub-150 millisecond latency enables truly responsive AI-driven narratives. For digital avatars and virtual humans, where voice latency matters more than voice quality, this breakthrough enables natural flowing conversations that were previously impossible. In education, real-time AI language tutors could make language learning more accessible and affordable. In customer service, near-instantaneous responses would allow users to interact with AI assistants more naturally, improving efficiency and satisfaction.
By developing more efficient multilingual models, we could enable real-time translation during fast-paced conversations, transforming global communication in business, travel, and diplomacy.
More important, this technology could transform how we interact with our devices. Under current approaches, a simple AI voice interaction can at times be incredibly slow, taking from three to five seconds to generate a response: with 0.5 to one second for speech recognition, from to one to two seconds for the LLM response, and from to one to two seconds for text-to-speech conversion. Some conversational AI companies can't use GPT yet because the latency is too high to wait for a whole sentence to generate. By reducing the total response time to just 0.6 seconds and spcifically achieving text-to-speech latency of 25 milliseconds, we can enable truly fluid conversations with AI. That would make it a preferable alternative to screen-based interactions, potentially reducing our dependence on visual interfaces and enabling more natural, intuitive digital engagement.
The Near- and Long-Term Impact
The next three to five years will be transformative for voice AI adoption. As latency barriers fall and model sizes continue to decrease, I expect to see key technical milestones, including comprehensive multilingual support, significant cost reductions, and deployment on edge devices. This will unlock immediate opportunities across multiple sectors, from conversational AI and enterprise sales to digital avatars and generative gaming.
Looking further ahead to the next decade, we'll see a deeper voice revolution that could fundamentally rewire human-machine interaction. The vision would be one where digital interaction becomes more natural and intuitive, reducing our reliance on screens and enabling more human-centric computing experiences. With language-agnostic models becoming more accessible and affordable, we could see voice AI democratized across markets, levelling the playing field rather than being monopolized by Big Tech.
Of course this transition will come with a need to proactively address challenges around privacy protection, deepfake prevention and ensuring equitable access across different languages and regions. The goal isn't just to make voice AI ubiquitous, but to ensure it speaks fairly and safely to, and for, everyone.
Sohaib Ahmad is co-founder and CEO of Neuphonic.