Granular Synthesis Haptic Conversion System
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Solution Overview
Problem
Haptic effects generated by existing technologies are often perceived as synthetic or artificial due to their method of generation, lacking authenticity and organic feel.
Innovation Solution
A system that converts audio or video data into haptic effects using granular synthesis, segmenting the data into waveforms, combining them with envelopes to create grains, and generating haptic effects based on these grains, which are then combined into a cloud to produce dynamic and authentic haptic feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If haptic effects are generated by combining periodic haptic signals or pre-processing received signals, then haptic effects can be produced in real-time, but the effects are perceived as synthetic or artificial
Solution Approach 1:
The input signal is segmented into multiple grains (small time segments), which are then processed individually and recombined. This segmentation allows the system to maintain real-time processing capability while creating more natural-sounding haptic effects through the granular synthesis approach, resolving the contradiction between real-time generation and authenticity.
Solution Approach 2:
The patent introduces an intermediary processing stage where grains are created from the input signal, allowing transformation of the original signal into a form that can be manipulated to sound more natural. This intermediary grain-based representation serves as a mediator between the raw input and the final haptic output, improving authenticity while maintaining real-time processing.
2Reliability
If granular synthesis is used to create authentic haptic effects, then the haptic feedback becomes more natural and organic, but the processing complexity increases
Solution Approach 1:
By segmenting the signal into grains, the complex task of creating natural haptic effects is broken down into manageable units. Each grain can be processed independently with simpler operations, and the overall complexity is reduced through this divide-and-conquer approach while still achieving authentic results.
Solution Approach 2:
The patent applies parameter changes to the grains (such as amplitude modulation, frequency modulation, and timing variations) to create natural-sounding haptic effects. By manipulating these parameters on individual grains rather than the entire signal, the processing complexity is managed while achieving the desired authenticity.
3Duration of action of moving object
If multiple grains are combined to form a cloud, then dynamic and evolving haptic effects are achieved, but the computational requirements increase
Solution Approach 1:
The signal is divided into multiple grains that can be independently managed and processed. This segmentation allows the system to create evolving haptic effects through the interaction of multiple grains over time, while the modular nature of grain processing helps manage computational energy requirements by allowing selective processing of individual grains.
Solution Approach 2:
The patent employs periodic actions in the form of grains that are generated, processed, and combined in a rhythmic manner. This periodic grain-based approach creates dynamic and evolving haptic effects over time while maintaining a structured processing pattern that helps optimize computational energy usage compared to continuous processing.
Data Source
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AI summary
A system is provided that converts an input, such as audio data, into one or more haptic effects. The system applies a granular synthesis algorithm to the input in order to generate a haptic signal. The system subsequently outputs the one or more haptic effects based on the generated haptic signal. The system can also shift a frequency of the input, and also filter the input, before the system applies the granular synthesis algorithm to the input.