Voice-Based Control for Sexual Stimulation Devices
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Solution Overview
Problem
Current control systems for sexual stimulation devices are rudimentary and primarily limited to pre-programmed routines, requiring manual programming and physical or touch-screen controls, which can be cumbersome and distracting, lacking voice-based control options.
Innovation Solution
A system and method for voice-based control of sexual stimulation devices, involving the receipt and analysis of voice data to detect spoken commands and non-speech vocalizations, using machine learning algorithms to associate voice patterns with device controls, and generating control signals for customizable stimulation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual programming or physical controls are used, then device customization is possible, but operation becomes cumbersome and distracting
Solution Approach 1:
The patent replaces mechanical controls (buttons, knobs, touch screens) with voice-based control using acoustic field detection. The system uses microphones to capture voice commands and machine learning algorithms to interpret and execute them, eliminating the need for physical manipulation of controls during intimate moments.
Solution Approach 2:
The patent introduces voice as an intermediary between the user and the device control system. Instead of directly manipulating controls, users speak commands that are translated into control signals through acoustic detection and processing, providing a more natural and less distracting interface.
2Adaptability or versatility
If pre-programmed routines are used, then device operation is simplified, but adaptability to user preferences is limited
Solution Approach 1:
The patent implements dynamic control where the system adapts to user preferences in real-time through voice interactions. Instead of static pre-programmed routines, the device learns and adjusts stimulation parameters based on user feedback and voice commands, creating a personalized experience that evolves with user needs.
Solution Approach 2:
The system performs self-customization by automatically analyzing voice commands and learning user preferences without requiring manual programming. The machine learning algorithms enable the device to autonomously adjust settings based on voice-based feedback, reducing the need for user intervention in the programming process.
3Ease of operation
If voice-based control is implemented, then ease of operation improves, but device complexity increases
Solution Approach 1:
The patent employs a multi-functional control system that handles various control modes (pre-programmed, manual, voice-based) through a unified architecture. The same hardware platform supports multiple control methods, with the voice-based system sharing processing resources with existing control mechanisms, thereby managing complexity through functional integration.
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 automatic customization of stimulation based on user preferences with minimal input, providing a more intuitive and user-friendly control experience through voice commands and stress pattern detection.
Implementation Method 1
a microphone connected to the computing device and configured to receive audio and transmit the audio to the computing device
Data Source
AI summary
A system and method for voice-based control of sexual stimulation devices. In some configurations, the system and method involve receiving voice data, analyzing the voice data to detect spoken commands, and generating control signals based on the commands. In some configurations, the system and method involve receiving voice data, analyzing the voice data for non-speech vocalizations, detecting voice stress patterns, and generating control signals based on the detected patterns. In some configurations, the analyses of the voice data are performed by machine learning algorithms which may be trained on associations between speech and non-speech vocalizations of a user while the user engages in one or more voice-based training tasks, associating speech and non-speech vocalizations with controls of the sexual stimulation device. In some configurations, machine learning algorithms are used to make the associations. In some configurations, data from other biometric sensors is included in the associations.