Noise suppression in Human Spaceflight audio systems
Description
Noise. Is. Aggravating. Especially on voice and video calls. It’s certainly an unwelcome party to most conversations, but it has always been around.
Detailed example
noise suppression
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
Until recently Machine learning (ML) and artificial intelligence (AI) have led to highly elective noise-suppression and cancellation techniques, many of which are now being used at various levels of technology stacks: in hardware, middleware, apps, and more recently, SDKs (Software Development Kits) that are now available to a broad range of developers. The industries developing these new techniques and technologies have been mostly focused on standard use cases like call centers, telephony, simple voice, and video calls that power daily business meetings, calls with friends, family, and so forth. Recently, calls are no longer just calls—increasingly, they are becoming online rooms, virtual pods, or meeting spaces where people interact in new ways or take part in activities together.
Controls / human review
ATO: Not reported; PIA: Not published