Wearable EMG Sensors Augment Speech Recognition Accuracy
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Solution Overview
Problem
Existing speech recognition systems lack the ability to effectively incorporate contextual information from user movements and muscle activations, leading to suboptimal performance in accuracy and speed.
Innovation Solution
The integration of neuromuscular signals, recorded using electromyography (EMG) sensors, to augment speech data, allowing the system to interpret musculo-skeletal representations and modify operations such as formatting, punctuation, and interaction modes, thereby enhancing speech recognition performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If only speech data is used as input to the speech recognition system, then the system structure remains simple, but the speech recognition accuracy and speed are suboptimal
Solution Approach 1:
The patent combines speech data with neuromuscular signals (EMG data) from wearable sensors to create a hybrid input system. The speech recognizer processes both audio signals and neuromuscular signals simultaneously, merging multiple data sources to improve recognition accuracy while managing system complexity through integrated processing architecture.
Solution Approach 2:
The patent introduces neuromuscular signals as an intermediary that bridges the gap between user intent and speech recognition. The wearable EMG sensors detect muscle activations related to speech production, providing complementary information that enhances the speech recognizer's ability to accurately interpret speech, especially in challenging acoustic environments.
2Productivity
If only speech data is used as input, then the system operation remains simple, but the speech recognition speed is limited
Solution Approach 1:
The system merges speech data processing with neuromuscular signal processing to accelerate recognition. By parallel processing of both data types and combining their outputs, the system achieves faster and more accurate speech recognition compared to using speech data alone, as the neuromuscular signals provide additional constraints that reduce processing ambiguity.
3Measurement precision
If neuromuscular signals are integrated to augment speech data, then speech recognition accuracy improves, but the device complexity increases
Solution Approach 1:
The patent segments the speech recognition system into distinct functional modules: wearable EMG sensors for neuromuscular signal acquisition, signal processing components for extracting relevant features, and a speech recognizer that integrates multiple data sources. This modular segmentation manages complexity by allowing each component to be optimized independently while maintaining overall system accuracy.
Solution Approach 2:
The wearable device with EMG sensors serves multiple functions: detecting muscle activations related to speech production, providing contextual information about user state, and potentially controlling other device functions. This multi-functionality justifies the added complexity by providing multiple benefits from a single integrated system.
4Measurement precision
If neuromuscular signals are used for hybrid input modes, then control precision over speech recognition processes improves, but the ease of operation decreases
Solution Approach 1:
The system uses neuromuscular signals that occur naturally during speech production, requiring no additional user effort or training. The EMG sensors automatically detect muscle activations that accompany speech, providing control precision without increasing the ease of operation, as the system leverages existing physiological signals rather than requiring new user actions.
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
This approach improves speech recognition accuracy and speed by leveraging contextual information from user movements and muscle activations, enabling more precise control over speech recognition processes and hybrid input modes.
Implementation Method 1
a plurality of neuromuscular sensors arranged on one or more wearable devices. The plurality of neuromuscular sensors is configured to continuously record a plurality of neuromuscular signals from the user
Data Source
AI summary
Systems and methods for using neuromuscular information to improve speech recognition. The system includes a plurality of neuromuscular sensors, arranged on one or more wearable devices, wherein the plurality of neuromuscular sensors is configured to continuously record a plurality of neuromuscular signals from a user, at least one storage device configured to store one or more trained statistical models, and at least one computer processor programmed to provide as an input to the one or more trained statistical models, the plurality of neuromuscular signals or signals derived from the plurality of neuromuscular signals, determine based, at least in part, on an output of the one or more trained statistical models, at least one instruction for modifying an operation of a speech recognizer, and provide the at least one instruction to the speech recognizer.