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An octonion-based nonlinear echo state network for speech emotion recognition in Metaverse
Fatemeh Daneshfar1, Mohammad Behdad Jamshidi2
1Department of Computer Engineering, University of Kurdistan, Sanandaj, Iran.
Summary
This study introduces NO2GESNet, a novel echo state network (ESN) using octonion algebra to improve speech emotion recognition (SER) for Metaverse applications. The new method enhances signal processing and avatar-user interaction in virtual environments.
Area of Science:
- Artificial Intelligence
- Computer Science
- Signal Processing
Background:
- The Metaverse requires enhanced signal processing and pattern recognition for infrastructure.
- Speech Emotion Recognition (SER) is vital for Metaverse usability but faces challenges with avatar-user engagement and complex digital twin interactions.
- Existing Echo State Networks (ESNs) struggle with high-dimensional data and memory consumption, limiting their effectiveness in the Metaverse.
Purpose of the Study:
- To develop an efficient machine learning (ML) technique for hypercomplex signal processing to improve Metaverse platforms.
- To address the limitations of conventional ESNs in handling high-dimensional data and memory usage for SER in the Metaverse.
- To propose a novel ESN structure, NO2GESNet, leveraging octonion algebra for enhanced SER performance.
Main Methods:
- Developed NO2GESNet, a novel Echo State Network (ESN) structure utilizing octonion algebra.
- Incorporated a multidimensional bilinear filter to address ESN weaknesses in higher-order statistics presentation.
- Designed and analyzed three comprehensive scenarios for NO2GESNet application within the Metaverse.
Main Results:
- Octonion algebra enables compact high-dimensional data display, improving network precision and performance over conventional ESNs.
- The proposed NO2GESNet effectively overcomes ESN limitations in memory consumption and high-dimensional data processing.
- The analyzed scenarios demonstrate the accuracy and performance of NO2GESNet for SER in the Metaverse.
Conclusions:
- NO2GESNet offers a robust solution for SER in the Metaverse, enhancing user experience and platform tangibility.
- The novel network architecture improves the efficiency and effectiveness of ML-based signal processing for virtual environments.
- This research paves the way for more immersive and interactive Metaverse platforms through advanced SER capabilities.
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