Isolated Word Recognition System Using DTW Algorithm
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Resource Overview
An isolated word recognition system based on the Dynamic Time Warping (DTW) algorithm, implemented using MATLAB programming. The system performs endpoint detection on speech signals to extract effective speech segments from raw audio data, enabling accurate isolated word recognition through time-series pattern matching.
Detailed Documentation
The isolated word recognition system based on the Dynamic Time Warping (DTW) algorithm is a speech signal processing method implemented using MATLAB programming. This approach utilizes endpoint detection algorithms to extract effective speech segments from raw signals, achieving accurate recognition of isolated words through dynamic time alignment. The system typically implements frame-based processing with feature extraction (such as MFCC coefficients) and uses DTW to compare test patterns with reference templates while compensating for timing variations. This type of system can be applied in speech recognition technology research and practical applications, contributing to advancements in the speech processing field through MATLAB implementations that include functions for signal preprocessing, feature vector calculation, and dynamic programming-based distance measurement.
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