Silent Speech EMG Input for Private, Noise-Robust Interaction
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Solution Overview
Problem
Conventional interaction systems face limitations in practicality due to the need for text input via keyboards, which is impractical in noisy environments or where privacy is a concern, and voice-based systems are inadequate in noisy conditions or when silence is preferred.
Innovation Solution
A wearable speech input device using electromyography (EMG) sensors captures silent speech muscle activation patterns, which are processed by a speech model to generate text prompts, and a knowledge system uses this input to take actions or generate responses, optionally incorporating additional sensors and environmental context for improved accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If voice-based systems are used for user interaction, then ease of operation is improved, but reliability deteriorates in noisy environments
Solution Approach 1:
The patent replaces acoustic-based voice recognition with electromyographic (EMG) signal detection to capture speech muscle activation patterns. This substitution eliminates the vulnerability to environmental noise while maintaining the ease of hands-free operation, as users can speak naturally without worrying about background interference affecting recognition accuracy.
Solution Approach 2:
The patent introduces an intermediary layer between the user's speech production and the system's understanding. Instead of directly capturing sound waves (which are susceptible to noise), the system detects muscle activation patterns through EMG sensors, processes these signals through a speech model, and generates text output. This intermediary approach filters out noise while preserving the natural speech interaction.
2Reliability
If text input via keyboard is required, then reliability is improved, but ease of operation deteriorates
Solution Approach 1:
The patent replaces the mechanical keyboard input method with an EMG-based speech recognition system. Users can input text by speaking naturally, and the system converts their muscle activation patterns into text output, eliminating the need for physical keyboard interaction while maintaining accurate text input reliability.
Solution Approach 2:
The system enables users to perform text input without requiring manual keyboard operations. The EMG sensors automatically capture speech muscle patterns, and the integrated speech model processes these signals to generate text, allowing the system to serve itself in converting speech to text without requiring traditional input mechanisms.
3Ease of operation
If voice-based systems are used, then ease of operation is improved, but privacy concern worsens
Solution Approach 1:
The patent substitutes acoustic voice capture with EMG signal detection, which only measures muscle activation patterns without capturing audible sound. This eliminates the privacy risks associated with voice recording and transmission, as no audio data is collected or stored, while users can still speak naturally for input.
Solution Approach 2:
The patent extracts only the necessary information (muscle activation patterns) from the speech production process, completely separating the input mechanism from the audible output. By taking out the acoustic component and retaining only the muscular signal processing, the system maintains ease of operation while eliminating privacy vulnerabilities inherent in voice-based systems.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables users to interact silently with systems, enhancing privacy and usability in noisy environments by accurately converting silent speech into actionable inputs, improving interaction efficiency and accuracy through context-aware processing.
Implementation Method 1
the speech input device includes an electromyography (EMG) sensor, and the signal is an EMG signal captured from the EMG sensor when the user is silently speaking
Data Source
AI summary
The techniques described herein relate to computerized methods and systems for integrating with a knowledge system. In some embodiments, a user interaction system may include a speech input device wearable on a user and configured to receive an electronic signal indicative of a user's speech muscle activation patterns when the user is speaking. In some embodiments, the electronic signal may include EMG data received from an EMG sensor on the speech input device. The system may include at least one processor configured to use a speech model and the electronic signal as input to the speech model to generate a text prompt. The at least one processor may use a knowledge system to take an action or generate a response based on the text prompt. In some embodiments, the system may provide context to the knowledge system.