Gesture Input Translation System for Muted Voice Communication
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Solution Overview
Problem
Communication devices face challenges in noisy environments where users need to participate in voice calls while minimizing ambient noise interference, and existing systems struggle to translate inputs effectively when the mute function is active, especially when receiving devices lack text message or video conferencing capabilities.
Innovation Solution
An input translation system that obtains gesture definitions, detects the mute function, and translates gesture data into voice communications, allowing users to engage in voice dialogue while the mute function is active, without requiring receiving devices to have text message or video conferencing functionality, using devices like smart rings, contact lenses, or shoes to capture gestures and convert them into voice communications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If the mute function is activated to prevent ambient noise interference, then noise filtering is improved, but voice communication capability deteriorates
Solution Approach 1:
The patent introduces gesture recognition as an intermediary input method between the user and the communication system. When the mute function is active, users can perform gestures (detected by sensors like accelerometers or cameras) that are translated into voice communications, allowing communication without activating the microphone and thus without transmitting ambient noise
Solution Approach 2:
The patent replaces the traditional mechanical/acoustic input method (speaking into the microphone) with a gesture-based input system. Sensors detect physical gestures and convert them into digital signals that are then translated into voice communications, substituting the direct acoustic path with an electronic processing path that bypasses the mute restriction
2Ease of operation
If gesture recognition is implemented for input translation, then communication capability is improved, but device complexity increases
Solution Approach 1:
The patent leverages existing multi-functional components in communication devices. Cameras and sensors originally designed for other purposes (like video calls or motion detection) are repurposed for gesture recognition, avoiding the need for dedicated gesture input hardware and reducing overall system complexity
Solution Approach 2:
The system uses the device's own existing sensors and processing capabilities to perform gesture recognition and translation, rather than requiring external specialized equipment. The communication device serves its own input translation needs using its built-in resources
3Loss of information
If text message or video conferencing functionality is required on receiving devices, then input translation accuracy is improved, but device compatibility deteriorates
Solution Approach 1:
The patent introduces a server-based translation service as an intermediary that handles the complex translation processing remotely. The receiving device only needs to receive and play audio data, while the sophisticated gesture-to-voice translation is performed on the server, compatible devices don't need advanced text or video conferencing capabilities
Solution Approach 2:
The patent replaces the need for complex local processing on receiving devices with remote server-based processing. Instead of requiring receiving devices to have text message or video conferencing functionality for accurate translation, the system substitutes this with a simplified audio reception capability combined with server-side translation intelligence
Data Source
AI summary
A method can include obtaining one or more gesture definitions. Each of the one or more gesture definitions can identify a correspondence between a set of gestures and a voice communication. The method can further include detecting that a mute function of a communication device is active. The mute function can prevent the communication device from transmitting audio data to one or more receiving devices. The method can further include obtaining gesture data from one or more input devices. The method can further include identifying a first gesture definition of the one or more gesture definitions. The identifying the first gesture definition can be based on the gesture data. The method can further include initiating a transfer of a first voice communication to the one or more receiving devices. The first voice communication can correspond to the first gesture definition.