MATLAB Speech Recognition Implementation

Application Background

This MATLAB code performs speaker frequency analysis and processes recorded audio using digital signal processing techniques for playback. The primary application objective is to assist users in better understanding and utilizing audio data through systematic analysis and storage. By implementing audio analysis algorithms, users can gain deeper insights into acoustic characteristics for various application domains, including voice recognition systems and biometric authentication.

Key Technology

The implementation employs core signal processing technologies for audio data analysis. The Fourier Transform algorithm serves as a fundamental component, converting audio signals from time domain to frequency domain representation using MATLAB's fft() function, enabling comprehensive frequency characteristic analysis. Additionally, the code implements discrete sampling of analog signals through proper ADC (Analog-to-Digital Conversion) simulation, ensuring precise audio analysis and recording capabilities. The technical approach involves setting appropriate sampling rates and quantization parameters to maintain signal integrity during processing.

Through these key technologies, users can achieve comprehensive audio data understanding and utilization, providing accurate voice analysis and processing functionality for diverse application scenarios including voice pattern recognition and audio feature extraction.