Augmented Audio Conditioning System for Immersive Training
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing training resources are often expensive, limited in availability, and fail to recreate the dynamic, high-pressure environments necessary for effective performance conditioning, lacking dynamic feedback and realistic simulations of competitive scenarios.
Innovation Solution
An augmented audio conditioning system that recreates high-pressure performance environments through dynamic audio experiences, using sensors, machine learning, and audio data processing to simulate crowd noises and situational feedback, allowing users to train in a more immersive and realistic manner.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If expensive facilities and one-on-one coaching are used, then training quality and performance conditioning improve, but cost and accessibility worsen
Solution Approach 1:
The patent creates virtual copies of high-pressure performance environments through audio simulations. Instead of requiring users to physically attend expensive facilities with coaches, the system generates realistic audio recordings and simulations that replicate the sensory experience of competitive environments, making high-quality training accessible remotely and at lower cost
Solution Approach 2:
The patent replaces the mechanical system of physical coaching interactions and facility-based training with an automated audio-based system. Machine learning models generate and deliver personalized audio conditioning programs, substituting human coaches and physical facilities with intelligent software that provides equivalent training value
2Reliability
If traditional training resources are used, then some training benefit is achieved, but the ability to recreate dynamic high-pressure environments with dynamic feedback is insufficient
Solution Approach 1:
The patent implements dynamic audio environments that adapt in real-time to user performance. The system adjusts audio feedback, crowd noise, and environmental sounds based on detected user actions and performance metrics, creating a living, responsive training environment rather than static pre-recorded sessions
Solution Approach 2:
The patent incorporates multiple feedback loops where user actions are detected through sensors, processed by machine learning models, and immediately reflected in the audio environment. This creates closed-loop conditioning where users receive real-time auditory feedback that mirrors actual competitive responses, enhancing the realism and effectiveness of performance conditioning
Data Source
AI summary
Techniques for implementing an augmented audio conditioning (AAC) system are described herein. In some examples, the AAC system can store conditioning data comprising crowd noise experiences associated with context-relevant environments and/or actions associated with an activity. The AAC system can detect an action of a user who is training in a conditioning environment and determine that the action is associated with the activity. In some examples, the AAC system can also determine an association between the action of the user and audio data representing a crowd noise experience of a context-relevant environment during an event. Furthermore, the AAC system can, in response to detecting the action of the user, output the audio-conditioning data into the conditioning environment to simulate the crowd noise experience of the context-relevant environment during the event.