StableStream

StableStream is LansonAI's approach to maintaining readable continuity while live speech continues to evolve.

Real-time speech recognition produces changing information.

A naive interface can expose those changes directly:

we should probably
we should probably ship
we should probably ship the
we should probably ship this
we should probably ship this next
we should probably ship this next week

If earlier words are repeatedly replaced or rearranged, the interface may technically be updating quickly while becoming difficult to read.

StableStream addresses this boundary between model updates and human-readable output.

Ready to read, not racing to display

The fastest possible token is not always the most useful token.

A live interface must balance:

• response latency
• linguistic uncertainty
• correction quality
• visual stability
• reading continuity

StableStream is designed around that balance.

Its goal is to allow new information to arrive continuously without making previously presented information unnecessarily unstable.

Recognition stability and visual stability

These are related but different concepts.

Recognition stability describes how confident the system is that speech has been interpreted correctly.

Visual stability describes how much already-presented content moves or changes on screen.

A good live speech experience needs both.

StableStream operates at this boundary.

Application behavior

Applications consuming a live stream should distinguish between content that is still evolving and content that has become stable.

The API documentation describes the exact events and state transitions available to clients.

This page describes the underlying principle:

Live text should evolve without forcing the reader to repeatedly reconstruct what they have already understood.