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Natural Language Processing for Aviation Audio Communications

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SBIR / STTR

Contract Overview

Solicitation details, issuing organization, response deadlines, documents, and interested companies for this government contract opportunity.

AI Contract Overview

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The NASA SBIR/STTR Program is seeking a subcontractor to design and demonstrate the feasibility of utilizing speech-to-text and natural language processing to identify errors within controller-pilot communications. The primary objective of this effort is to implement transcription validation and error classification to improve the safety and accuracy of aviation audio communications. This project is designated as a Total Small Business Set-Aside under NAICS code 541713 and is managed by the National Aeronautics and Space Administration. Performance for this contract is centered at Moffett Field, California, with the official posting date listed as August 20, 2026.

General Info

NASA seeks a subcontractor for speech-to-text error identification in controller-pilot aviation communications.

Agency

National Aeronautics and Space Administration → NASA SBIR/STTR ProgramView Agency

NAICS

541713 - Research and Development in NanotechnologyView NAICS

Place of Performance

Moffett Field, CA, 94035, USA

Set-Aside

SBA

Documents

This scope was carved out of NASA-SBIR-154792.

The full solicitation package (1 document), including the RFP, is on the prime solicitation, not on this scope.

View the prime solicitation

System Wide Analysis Network for In-Time Safety Monitoring

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Timeline

PostedAug 20

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Organization & Contact Information

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AgencyNational Aeronautics and Space Administration → NASA SBIR/STTR Program

ContactsNo contacts available

OfficeN/A

Organization / Agency

National Aeronautics and Space Administration → NASA SBIR/STTR Program

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Office AddressN/A

ContactsNo contact information available

Full Description

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Design and demonstrate feasibility of using speech-to-text and NLP to detect errors in controller-pilot communications, including transcription validation and error classification.

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