Noise Addition and Filtering Processing on Speech Signals

Adding noise to speech signals is a fundamental signal processing operation. This process involves superimposing various types of noise onto clean speech signals to simulate real-world acoustic environments, which is crucial for testing and developing robust speech processing algorithms and techniques. The implementation typically involves generating noise signals (such as white Gaussian noise) and adding them to the original speech signal with controlled signal-to-noise ratios. Following noise addition, the contaminated speech signal undergoes filtering operations using three distinct filter types: low-pass filters (preserving frequencies below a cutoff threshold), band-pass filters (selecting specific frequency ranges), and high-pass filters (retaining frequencies above a cutoff point). These filters can be implemented using digital filter design methods like Butterworth, Chebyshev, or FIR filters, with MATLAB functions such as designfilt or butter for coefficient calculation. The filtering process modifies the frequency content of the signal to achieve different objectives like noise reduction, frequency band isolation, or signal enhancement. During program execution, special attention must be paid to audio file path configuration. The code should include proper file path validation and error handling mechanisms (using try-catch blocks or isfile checks) to ensure correct audio file loading and processing. Incorrect path specifications will result in file I/O errors and program termination. Therefore, when implementing speech signal processing systems, developers must incorporate robust path handling routines and clear error messages to guarantee smooth program operation.