NASA · NASA-279 · record R0183

Noise suppression in Human Spaceflight audio systems

National Aeronautics and Space Administration · JSC: Johnson Space Center

Overview

Development stage: In development or acquisitionSource: a) Pre-deployment – The use case is in a development or acquisition status.
High-impact designation: Not high-impactSource: c) Not high-impact
Impact justification: Not reported
Start date: Not reported
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Science
Operational functions: No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

Noise. Is. Aggravating. Especially on voice and video calls. It’s certainly an unwelcome party to most conversations, but it has always been around.

Expected benefits

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.

System outputs

noise suppression

Technology

AI classification: Classical / predictive MLSource: Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relatio…
System name(s): Not reported
Custom-developed code: Not reported
Public source code: Not reported

Sourcing

How it was built: Not reported
Vendor (as reported): Not reported
Vendors (standardized): None on the standard list

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII: Not reported
Privacy Impact Assessment: Not reported
Authorization to Operate: Not reported
Demographic features: Not reported
Training and evaluation data: Not reported
Federal Data Catalog: Not reported

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Pre-deployment testingNo answer reported

AI impact assessmentNo answer reported

Independent reviewNo answer reported

Ongoing monitoringNo answer reported

Operator trainingNo answer reported

Fail-safeNo answer reported

Appeal processNo answer reported

User and public consultationNo answer reported

Potential impacts and how they were identified

Not reported