Enhancing Speech Signal Clarity through Signal Noise Removal Using the LMS Algorithm

Speech communication applications like speech recognition and speech enhancement currently face challenges in reducing noise in audio or speech signals. Noise is added to the audio signal for a number of unavoidable reasons, making it challenging to hear. To reduce noise, various filtering techniques are used. The effectiveness of specific noise reduction algorithms can be impacted by the filter characteristics you use. This paper presents a speech denoising approach using the Least Mean Squares (LMS) algorithm. The algorithm is implemented on a noisy audio signal, generated by introducing white Gaussian noise (AWGN) to the audio under analysis. Results from both time and frequency domains affirm the efficacy of the LMS algorithm in reducing noise from the speech signal.