Artificial Speech Perception Processing System for Sound Recognition
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Solution Overview
Problem
Current technologies for global sound perception in the acoustic AT space are inadequate, as existing NLP systems fail to effectively capture and process sound and psychoacoustic entities, leading to limitations in sound recognition and memory storage.
Innovation Solution
The development of a bio digital twin technology that simulates the cognitive process of sound perception by transducing physical sound into sound memory, using a segmented system with a waveform computer-encoding engine to create artificial substitution codes for cataloging and processing auditory entities, integrating with existing NLP and deep learning technologies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing NLP systems are used to capture sound and psychoacoustic entities, then language processing capability is maintained, but sound recognition accuracy and memory storage effectiveness deteriorate
Solution Approach 1:
The system segments sound processing into distinct functional modules: a waveform computer-encoding engine for initial sound capture and encoding, an artificial speech perception processing system for cognitive simulation, and a global acoustic memory directory for structured storage. This segmentation allows each module to specialize in specific aspects of sound processing, improving overall accuracy while preventing information loss through dedicated optimization of each stage.
Solution Approach 2:
The patent introduces an intermediary artificial speech perception processing system that bridges the gap between raw sound capture and NLP processing. This intermediary layer simulates human cognitive processes for sound perception, transforming physical sound waves into cognitively-represented sound memory that preserves psychoacoustic characteristics while being compatible with existing NLP systems.
2Measurement precision
If a bio digital twin system simulates cognitive sound processing in real-time, then speech perception accuracy is improved, but system complexity increases
Solution Approach 1:
The complex bio digital twin system is divided into manageable segments: the waveform computer-encoding engine handles low-level signal processing, the artificial speech perception processing system simulates cognitive functions, and the global acoustic memory directory manages data storage. This segmentation reduces overall system complexity by distributing computational tasks across specialized modules with defined interfaces.
Solution Approach 2:
The patent replaces complex mechanical or hardware-based sound processing systems with software-based artificial speech perception processing that simulates cognitive functions. This substitution reduces physical system complexity while maintaining or improving speech perception accuracy through sophisticated algorithms that model human auditory processing.
3Loss of information
If artificial substitution codes are generated for cataloging auditory entities, then information organization is improved, but processing time increases
Solution Approach 1:
The system performs preliminary encoding of sound waves into artificial substitution codes at the waveform computer-encoding engine stage, before the main speech perception processing occurs. This preliminary action organizes information in advance using compressed spectral representations, reducing the computational burden during subsequent processing stages and minimizing overall processing time while maintaining effective information organization.
Solution Approach 2:
The patent transforms sound information from time-domain waveforms to frequency-domain spectral representations through the artificial substitution coding process. This parameter transformation compresses the information more efficiently, allowing for better organization in the global acoustic memory directory while reducing the time required for subsequent search and retrieval operations.
Data Source
AI summary
Systems and methods are herein provided for an artificial speech perception processing system. In one example, an artificial speech perception processing system comprises a waveform computer-encoding engine configured to generate referent code and metadata, an utterance harvesting process, and an administration including an installed base configured to test the referent code and metadata against the installed base.