Dynamic Speech Recognition Model Configuration for Aircraft
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Solution Overview
Problem
Existing speech recognition systems in aircraft environments face challenges in balancing accuracy and latency, leading to a tradeoff that compromises user experience due to their design-time constraints, which are not adaptable to individual pilot preferences or operational contexts.
Innovation Solution
A user-configurable speech recognition system that allows pilots to dynamically adjust the tradeoff between recognition accuracy and latency using a slider interface, selecting from various model configurations based on user-defined performance settings, which can be context-sensitive and specific to flight phases or onboard systems, utilizing combinations of acoustic and language models to optimize performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If speech recognition accuracy is increased, then user experience is improved, but latency increases which degrades user experience
Solution Approach 1:
The system dynamically adjusts speech recognition model configurations based on real-time operational context, flight phases, and user preferences. Multiple model configurations are maintained with different accuracy-latency tradeoffs, and the system switches between them dynamically rather than using a fixed configuration, resolving the contradiction by making the system adaptive to changing requirements
Solution Approach 2:
The system changes key parameters of the speech recognition model including vocabulary size, grammar complexity, and processing depth based on the operational context. By adjusting these parameters, the system can optimize for either accuracy or latency depending on the situation, eliminating the need to permanently choose one over the other
2Measurement precision
If speech recognition model complexity is increased to improve accuracy, then recognition performance is improved, but system resource consumption and processing time increase
Solution Approach 1:
The speech recognition system is divided into multiple separate model configurations, each optimized for specific accuracy requirements. Instead of using one complex model for all scenarios, the system segments the recognition task into multiple specialized models that can be selected based on the operational context, reducing the complexity burden on any single model
3Ease of operation
If fixed speech recognition models are used at design time, then system simplicity is maintained, but adaptability to individual pilot preferences and operational contexts is reduced
Solution Approach 1:
The system maintains multiple speech recognition model configurations that can serve different operational contexts and user preferences. This multi-functionality allows a single system to adapt to various scenarios (different flight phases, different pilots' preferences, different operational requirements) without requiring separate dedicated systems for each case
Data Source
AI summary
Methods and systems are provided for assisting operation of a vehicle using speech recognition. One method involves identifying a user-configured speech recognition performance setting value selected from among a plurality of speech recognition performance setting values, selecting a speech recognition model configuration corresponding to the user-configured speech recognition performance setting value from among a plurality of speech recognition model configurations, where each speech recognition model configuration of the plurality of speech recognition model configurations corresponds to a respective one of the plurality of speech recognition performance setting values, and recognizing an audio input as an input state using the speech recognition model configuration corresponding to the user-configured speech recognition performance setting value.