Voice Recognition Pipeline for Autonomous Electric Aircraft Flight Plans
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Solution Overview
Problem
Existing autonomous electric aircraft lack the ability to autonomously adjust flight plans based on real-time communication from ground control without human intervention.
Innovation Solution
Implementing a computing device with voice recognition capabilities using machine learning to receive voice data, transcribe it into text, extract queries, generate communication outputs, and adjust flight plans accordingly, enabling autonomous flight path adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If voice recognition system is implemented for autonomous flight adjustments, then automation capability is improved, but device complexity increases
Solution Approach 1:
The voice recognition system is divided into separate functional modules: voice data reception module, transcription module, query extraction module, communication output generation module, and flight plan adjustment module. Each module handles a specific aspect of the voice-to-flight-plan adjustment process, making the complex system manageable and maintainable while achieving high automation capability
Solution Approach 2:
The system introduces intermediate processing layers between voice data reception and flight plan adjustment. The transcription module converts voice data to text, the query extraction module identifies relevant information, and the communication output generation module formulates responses before adjusting flight plans. These intermediaries simplify the overall system architecture by breaking down complex processing into discrete stages
2Speed
If real-time voice data processing is implemented, then response time is improved, but computational energy consumption increases
Solution Approach 1:
The system performs preliminary processing of voice data in advance, including transcription to text and extraction of queries before flight plan adjustments are needed. This allows the system to be ready for rapid response when actual flight adjustments are required, reducing real-time computational burden and energy consumption while maintaining fast response capability
Solution Approach 2:
The system processes only the necessary portions of voice data required for flight plan adjustments rather than analyzing all possible speech content. By focusing computational resources on extracting relevant flight-related information and generating appropriate communication outputs, the system achieves fast response times while minimizing unnecessary energy consumption
Data Source
AI summary
A system for voice recognition in autonomous flight of an electric aircraft that includes a computing device communicatively connected to the electric aircraft configured to receive at least a voice datum from a remote device, wherein the voice datum is configured to include at least an expression datum, generate, using a first machine-learning process, a transcription datum as a function of the at least a voice datum, extract at least a query as a function of the transcription datum, generate, using a second machine-learning process, a communication output as a function of the at least a query, and adjust a flight plan as a function of the communication output.