The earliest ideation didn’t start with code, but with a question: How could technology make cabin communication more inclusive? The work reflects a growing shift toward more human-centered, inclusive cabin technologies and prototyping to demonstrate concepts early.
“We needed to understand the user’s perspective before diving into the technology,” said Amy Goodell, principal investigator. “You have to identify the right problems in order to come up with the right solutions.”
Above the noise
The STT concept emerged as Boeing engineers and research scientists began to collaborate.
Jinri Kim, a machine learning researcher at the Boeing Korea Engineering & Technology Center (BKETC), recalls how a simple idea gained momentum.
“Developing the prototype, we had to select a model that could understand context — what’s a crew announcement and what isn’t,” said Kim.
Aircraft cabins present serious technical challenges, including persistent engine noise, overlapping audio sources and limited Wi-Fi connectivity. To meet those constraints, the BKETC AI team evaluated multiple open-source architectures and adapted a model to work in noisy, offline conditions. The system processes incoming audio in two-second chunks, allowing near-real-time captions to appear on local devices or embedded displays.
“We had to avoid hallucination,” said Kim, referring to how AI sometimes generates plausible but incorrect output. “In-flight systems don’t have the luxury of guessing.”
“We selected models that could handle noisy input,” explained Jihyun Kim, a BKETC data scientist. “You can’t assume a clean signal on board.”