Wearable Speech Sentiment Analysis with Real-Time Visual Feedback
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Solution Overview
Problem
Individuals are often unaware of the emotional state they convey through their speech, which can impact interactions and relationships, as traditional feedback relies on constant presence of a friend or observer.
Innovation Solution
A system that processes a user's speech to determine emotional sentiment data using wearable devices and neural networks, providing real-time feedback through a user interface with visual indicators and descriptors, allowing users to adjust their behavior.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional feedback methods are used, then social interaction quality is improved, but device complexity and accessibility are worsened due to requiring constant presence of a friend or observer
Solution Approach 1:
The system enables self-service by allowing users to autonomously monitor their own emotional states through speech analysis. The wearable device automatically captures audio, processes it through neural networks, and provides feedback without requiring external observers or friends to be constantly present, thus resolving the contradiction between feedback reliability and system complexity
Solution Approach 2:
The patent introduces an intermediary system consisting of wearable devices, neural networks, and processing units that mediate between the user's speech and the feedback output. This intermediary layer automates the feedback process, eliminating the need for direct human observation while maintaining accurate emotional state detection and communication
2Speed
If real-time speech processing is implemented, then feedback timeliness is improved, but energy consumption and device resource usage are worsened
Solution Approach 1:
The system segments the speech processing task into distinct components: audio capture by the wearable device, neural network processing, and feedback generation. This segmentation allows each component to be optimized independently, enabling real-time processing while managing energy consumption through efficient task distribution and processing only when necessary
Solution Approach 2:
The system employs periodic action by activating the speech processing functions only when needed rather than continuously. The wearable device monitors for speech events and triggers processing only during relevant periods, maintaining real-time feedback capability while significantly reducing overall energy consumption compared to continuous operation
3Productivity
If continuous speech monitoring is performed, then emotional feedback availability is improved, but user privacy concerns and data security risks are worsened
Solution Approach 1:
The system extracts and processes only the necessary emotional state information from continuous speech monitoring rather than storing or exposing the complete speech data. By taking out only the essential features needed for emotional analysis and discarding the rest, the system maintains high feedback availability while minimizing privacy risks through data minimization
Solution Approach 2:
The patent applies the principle of disposable data by processing speech information temporarily and discarding it after use, rather than storing it long-term. The emotional state data is extracted, used for immediate feedback, and then discarded, reducing the persistence of sensitive information and thereby lowering privacy risks while maintaining continuous feedback availability
Data Source
AI summary
A microphone acquires audio data of a user's speech. The audio data is processed to determine sentiment data indicative of perceived emotional content of the speech. For example, the sentiment data may include values for one or more of valence that is based on a particular change in pitch over time or activation that is based on speech pace. A simplified user interface provides the user with a graphical representation based on the sentiment data and associated descriptors. For example, a visual indicator such as a dot may be shown at particular coordinates onscreen that correspond to the sentiment data. Text descriptors may also be presented near the dot. As the user continues speaking, and new audio data is processed, the interface is dynamically updated. The user may use this information to assess their state of mind, facilitate interactions with others, and so forth.