Depth Camera Gesture Context for Speech Recognition Ambiguity
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Solution Overview
Problem
Voice recognition systems in vehicles face ambiguity due to shared verbal commands across different devices, leading to unintended operations and decreased user experience, as the context of user commands is not properly identified.
Innovation Solution
A computer-implemented method using a depth camera to capture images of a user's pose or gesture, processing this information to select appropriate verbal commands associated with targeted devices, thereby enhancing the accuracy of speech recognition by determining the context of user inputs based on the location of their hands or forearms relative to the camera.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If speech recognition is used to operate vehicle devices, then hands-free operation is improved, but command ambiguity increases due to shared verbal commands across different devices
Solution Approach 1:
The patent introduces gesture recognition as an intermediary mechanism between the user and speech recognition systems. By detecting hand gestures and their spatial positions, the system determines contextual information about which device the user intends to control. This intermediary layer resolves the ambiguity of shared verbal commands by providing device-specific context, thereby maintaining hands-free operation while improving command accuracy.
2Adaptability or versatility
If multiple devices share similar verbal commands, then system versatility is improved, but command disambiguation becomes more difficult
Solution Approach 1:
The patent adds a spatial dimension to command recognition by incorporating gesture position data. Instead of relying solely on verbal commands, the system detects the three-dimensional position of the user's hand gestures and uses this spatial information to determine which device context is intended. This dimensional addition allows multiple devices to share verbal commands while maintaining clear disambiguation through spatial context.
3Measurement precision
If gesture recognition is added to speech recognition, then command accuracy is improved, but system complexity increases
Solution Approach 1:
The patent segments the command recognition system into distinct functional modules: gesture detection module, speech recognition module, and command disambiguation module. Each module handles a specific aspect of the recognition process independently. The gesture detection module captures hand position data, the speech recognition module processes verbal commands, and the disambiguation module integrates both inputs to determine the intended device. This segmentation improves accuracy while managing system complexity through modular design.
Data Source
AI summary
A method or system for selecting or pruning applicable verbal commands associated with speech recognition based on a user's motions detected from a depth camera. Depending on the depth of the user's hand or arm, the context of the verbal command is determined and verbal commands corresponding to the determined context are selected. Speech recognition is then performed on an audio signal using the selected verbal commands. By using an appropriate set of verbal commands, the accuracy of the speech recognition is increased.