Aircraft Speech Intelligibility Analysis Using Signal Recording
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Solution Overview
Problem
Current methods for determining speech intelligibility in aircraft require dedicated flight time and resources, especially human-based testing methods like the Modified Rhyme Test, which are costly and resource-intensive, while machine-based methods like STI require expensive airborne testing.
Innovation Solution
A system and method that combines a machine-based speech evaluating signal with in-flight noise representation to determine speech intelligibility without the need for airborne testing, using a ground-based and in-flight signal receiving unit to analyze and present the combined noise signal, allowing for speech intelligibility assessment during flight operations without dedicated flight time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If human-based testing procedures like the Modified Rhyme Test are used to evaluate speech intelligibility, then measurement precision is improved, but device complexity and loss of time increase due to requiring dedicated test airplanes and extended flight time
Solution Approach 1:
The patent replaces human-based mechanical testing procedures with an automated machine-based signal processing system. The STI signal generator automatically generates test signals, and the signal processor automatically analyzes the received signals to compute speech intelligibility metrics, eliminating the need for human listeners and manual test procedures while maintaining measurement accuracy
Solution Approach 2:
The system performs self-testing by automatically generating test signals, recording the received signals, processing the data, and computing speech intelligibility metrics without requiring human operators during flight. The dedicated test airplane serves itself by using its own communication systems and noise environment to evaluate speech intelligibility
2Productivity
If machine-based STI testing is conducted during flight operations, then productivity is improved by eliminating dedicated test flights, but measurement precision may deteriorate without proper airborne testing
Solution Approach 1:
The system performs preliminary recording of in-flight noise and communication system signals during regular flight operations. These recordings are then processed after the flight to compute speech intelligibility metrics, allowing the testing to be done without dedicating flight time while ensuring accurate measurements of the actual flight environment
Solution Approach 2:
The patent uses recorded signal representations as intermediaries. Instead of requiring real-time airborne testing, the system records the actual communication signals and noise during flight, then uses these recordings as intermediaries to perform the speech intelligibility analysis in a controlled environment, preserving measurement accuracy while eliminating the need for dedicated test flights
3Measurement precision
If dedicated flight time is allocated for speech intelligibility testing, then measurement precision is improved through actual airborne testing, but loss of time increases for flight operations
Solution Approach 1:
The system performs preliminary recording of all necessary signals (communication signals and in-flight noise) during regular flight operations. The actual speech intelligibility computation is then performed after the flight using these pre-recorded signals, eliminating the need to allocate dedicated flight time while ensuring measurements are taken in the actual flight environment
Solution Approach 2:
The patent separates the data collection phase from the analysis phase. Signal recording is segmented and performed during regular flight operations, while the computationally intensive speech intelligibility analysis is segmented and performed separately after the flight, allowing both phases to occur without interfering with flight schedules
Data Source
AI summary
A method for effecting a machine-based determination of speech intelligibility in an aircraft during flight operations includes: (a) in no particular order: (1) providing a representation of a machine-based speech evaluating signal; and (2) providing a representation of in-flight noise; (b) combining the representation of a machine-based speech evaluation signal and the representation of in-flight noise to obtain a combined noise signal; and (c) employing the combined noise signal to present the machine-based determination of speech intelligibility in an aircraft during flight operations.