How Devices Learn to Truly Listen: Insights from Unite.AI Interview

Voice assistants have gotten impressive at party tricks—writing, drawing, composing. But when you talk to your devices, they still often miss the point. They fail in noisy rooms, with overlapping speakers, and in the messy reality of homes, cars, and workplaces.

In a recent in‑depth interview with Unite.AI, Kardome CEO and Co‑founder Dani Cherkassky shared how we’re closing that gap with Spatial Hearing AI and Cognition AI—so devices and robots can truly listen like humans, but better.

From Lab Magic to Real-World Frustration

Dani Cherkassky and co‑founder and CTO Alon Slapak started Kardome out of both fascination and frustration.

• In quiet labs, modern speech recognition looked almost perfect.
• But in a noisy car, busy office, or chaotic home, performance collapsed to 1990s levels.
• Voice is the most natural interface for humans, but technology forces people to speak like machines: fixed commands, repetition, “voice etiquette.”

That disconnect became Kardome’s mission: build technology that works where people actually live and work, not just in controlled demos.

Why Conventional Voice UI Fails in Real Environments

Most current voice interfaces rely on a simplified model of the world:

• Multiple microphones are used mainly to estimate the direction of arrival.
• Reverberation (sound bouncing off walls, windows, and objects) is treated as noise.
• In real rooms, a single voice looks at the system like it’s coming from hundreds of directions at once.

Dani describes this as an “acoustic hall of mirrors:”

• The system can’t tell direct voice from reflections.
• It loses track of who is speaking and where they are.
• Accuracy degrades sharply as soon as you leave the lab.

As long as voice AI is effectively direction‑only and cloud‑dependent, it will keep struggling in real-world, multi-speaker environments.

Spatial Hearing AI: Treating Every Speaker as the Only One in the Room

Kardome’s key breakthrough is Spatial Hearing AI.

Instead of just estimating direction, the technology:

• Analyzes the full 3D reflection pattern a voice creates in a space.
• Treats that pattern as an acoustic fingerprint for a specific location.
• Instantly infers where each speaker is in three-dimensional space.

Where conventional systems get confused by reflections, Kardome uses them as signal:

• A Kardome‑enabled device can focus on one person in a noisy environment.
• It hears that person as if they were alone in a quiet room.
• Multiple speakers can interact naturally without the system collapsing.

On top of this, Cognition AI understands:

• Who is speaking.
• What they mean, in conversational context.
• How to maintain dialogue flow across turns and interruptions.

Together, Spatial Hearing AI and Cognition AI form the sensory and cognitive stack needed for truly natural voice interaction.

The Coming 'iPhone Moment' for Voice – Led by Robotics

In the interview, Dani describes voice AI’s “iPhone moment” as the point where:

• Voice has become the default interface for computers and devices.
• People expect to speak naturally to almost any product.

He sees several drivers:

• Cars adopt voice for safety and usability.
• Smart homes and consumer electronics add voice where screens don’t make sense.
• Robotics becoming the real inflection point:
  • As robots move into homes and workplaces, voice becomes the only interface that scales.

For this to work, robots and devices need:

• Precise spatial awareness—knowing exactly who is addressing which device.
• Real conversational understanding, not just wake words and short commands.
• Edge‑native intelligence so interaction is instant, private, and reliable.

Edge-First Voice AI: Privacy Without Sacrificing Performance

Most current solutions rely heavily on cloud processing:

• Always‑listening microphones send data to the cloud.
• Privacy concerns and cost limit how much can be processed continuously.
• That limitation blocks truly conversational, always‑on experiences.

Kardome takes a different approach:

• Move as much intelligence as possible to the edge device itself.
• Use Spatial Hearing AI and local language models to:
  • Analyze the acoustic scene in real time on the device.
  • Keep sensitive voice data from ever leaving the device.
  • Enable always‑listening, high‑quality Voice UI without cloud dependence.

This removes the trade‑off between privacy and performance and enables new classes of “ambient” voice experiences.

What This Unlocks for Devices and Robots

Dani highlights how Spatial Hearing AI and Cognition AI can reshape everyday products:

• Cars
  • Truly hands‑free control at highway speeds, with music and passengers talking.
  • Clear focus on the driver or the right passenger when multiple people speak.
• Smart homes & consumer electronics
  • Devices that distinguish speakers in a room and respond to the right person.
  • Multiple simultaneous requests are handled gracefully instead of breaking the system.
• Wearables & public spaces
  • Isolate the wearer’s voice in crowded environments.
  • Deliver personalized but private interactions in shared spaces.
• Robotics
  • Robots that understand conversational context and turn‑taking.
  • Natural, multi‑speaker interaction in homes, offices, and industrial settings.

The common thread: devices stop forcing users to adapt to technology and start adapting to human communication.

Looking Ahead: From Novelty to Voice-First Computing

Five years from now, Dani expects voice AI to be:

• As ubiquitous as touchscreens and keyboards.
• Embedded across robots, smart glasses, cars, and everyday devices.

The real milestone won’t be a specific model or feature. It will be behavior:

• People stop thinking about “voice commands” and simply talk.
• Multi-user environments “just work.”
• Children grow up expecting any device to understand them naturally.

Kardome’s goal is to be the operating layer for voice interaction in those environments—making it possible to operate any device by voice, in any space, with human‑level listening.

Explore the Full Conversation

This recap only scratches the surface of the Unite.AI discussion.

To dive deeper into:

• How Spatial Hearing AI works under the hood
• Why edge‑native voice is critical for privacy and performance
• What it will take to reach true voice‑first computing

You can read the full Unite.AI interview with Dani Cherkassky.

But the best way to understand Kardome is to see and hear it in person.

See Human Voice AI in Action at CES

Heading to CES?

We’ll be demonstrating how Spatial Hearing AI and Cognition AI let devices and robots:

• Focus on the right speaker in noisy environments
• Handle overlapping speech without breaking
• Enable natural, frustration‑free interaction in real‑world conditions

Book a 20‑minute CES session with our team to experience Kardome live and talk through your 2026 roadmap for voice in devices and robotics.