音节识别方法以及相关设备
By using a multi-resolution syllable recognition model to perform hierarchical processing and feature enhancement on EEG signals, the problem of insufficient accuracy in syllable recognition in existing technologies is solved, and accurate recognition of complex EEG activity patterns is achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SHENZHEN READLINE BIOTECH CO LTD
- Filing Date
- 2024-09-13
- Publication Date
- 2026-07-17
AI Technical Summary
Existing syllable recognition methods are limited by their linear characteristics, making it difficult to effectively model complex, nonlinear relationships, resulting in insufficient accuracy in analyzing the brain's response to visual or auditory stimuli.
A multi-resolution syllable recognition model is adopted, which performs hierarchical processing and feature enhancement on EEG signals through a time-scale hierarchical module and a representation enhancement module. Combined with comprehensive analysis of time and space scales, the accuracy of syllable recognition is improved.
By decomposing the data into multiple time and space levels for multi-layered analysis of spatiotemporal characteristics, complex EEG activity patterns are captured, improving the accuracy and precision of syllable recognition.
Smart Images
Figure CN121658800B_ABST