Speech Application Control With EMG, Facial Cues, And Gestures
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Solution Overview
Problem
Existing systems for interacting with computer-based systems are limited in efficiency and effectiveness, particularly when it comes to silent speech and non-verbal user inputs, leading to suboptimal interaction quality and speed.
Innovation Solution
A system and method that utilizes EMG sensors and other bio-sensors to detect and process silent speech, facial expressions, and gestures to enhance user interaction by providing real-time feedback and control, integrating machine learning models to improve system responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional speech recognition systems are used for user interaction, then the system can process verbal commands, but it cannot detect or process non-verbal inputs such as silent speech, facial expressions, and gestures
Solution Approach 1:
The patent combines multiple sensor types (microphones for acoustic speech, EMG sensors for facial muscle activity, and cameras for gesture detection) into a unified interaction system. This merging of different sensing modalities enables the system to process both verbal and non-verbal inputs simultaneously, resolving the contradiction by expanding input versatility while managing complexity through integrated processing architecture.
Solution Approach 2:
The system is designed to handle multiple input types through a single unified interface. The same system can process spoken commands, silent speech, facial expressions, and gestures, making it universally applicable to various user interaction scenarios. This multi-functionality approach allows one system to serve multiple purposes without requiring separate specialized systems for each input modality.
2Adaptability or versatility
If multiple sensor types are integrated to detect speech, facial expressions, and gestures, then interaction versatility improves, but device complexity increases
Solution Approach 1:
The system divides the detection task into separate modules, with each sensor type handled by a dedicated processing component. Speech processing, facial expression analysis, and gesture recognition are segmented into independent functions that can be processed separately and then integrated. This segmentation reduces the complexity of managing multiple sensor types by organizing them into manageable functional units.
Solution Approach 2:
The patent introduces an intermediary processing layer that receives data from multiple sensor types and consolidates it into a unified representation of user intent. This intermediary component acts as a mediator between the diverse sensor inputs and the final system response, simplifying the integration process by providing a standardized interface for handling multiple input modalities.
3Speed
If real-time detection of facial expressions and gestures is implemented, then interaction speed improves, but processing time and computational requirements increase
Solution Approach 1:
The system performs preliminary processing of sensor data by continuously analyzing facial expressions and gestures even before complete speech input is received. This preliminary action allows the system to anticipate user intent and prepare responses in advance, reducing the overall processing time needed for complete interaction while maintaining real-time responsiveness.
Solution Approach 2:
The system maintains continuous detection and processing of facial expressions and gestures throughout the interaction, rather than processing them in discrete batches. This continuous action ensures that the system is always ready to respond to changes in user expression or gesture, minimizing idle processing time and maintaining optimal interaction speed throughout the entire conversation.
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 more efficient and seamless interaction with computer-based systems by incorporating non-verbal cues, allowing for improved control and feedback mechanisms, enhancing the accuracy and responsiveness of systems like digital assistants.
Implementation Method 1
the component configured to detect the facial expression, tone, and/or gesture of the user is responsive to at least one EMG signal measured by a sensor in contact with the user
Data Source
AI summary
Methods and systems are provided for detecting and processing gestures, expressions (e.g., facial), tone and/or gestures of the user for the purpose of improving the quality and speed of interactions with computer-based systems. Such information may be detected by one or more sensors such as, for example, electromyography (EMG) sensors used to monitor and record electrical activity produced by muscles that are activated. Other sensor types may be used, such as optical, inertial measurement unit (IMU), or other types of bio-sensors. The system may use one or more sensors to detect speech alone or in combination with gestures, expressions (e.g., facial), tone and/or gestures of the user to provide input or control of the system.