Exploring the potential of parallel adaptive filters for audio noise removal

Abstract

This paper presents a novel adaptive structure for audio noise removal, aiming to enhance the performance of noise reduction. The proposed structure consists of a bank of parallel least-mean-squares, time-domain adaptive filters. Multiple microphones are employed to capture the noise source signal, while another microphone records the corrupted speech signal. By passing the recorded noise signals through the parallel adaptive filter bank structure and subtracting the results from the speech signal, the noise is effectively suppressed. Additionally, the noise removal performance is further improved by linearly combining the error signals, which include the noise-free speech signal. The effectiveness of the proposed adaptive structure is demonstrated through theoretical analysis and numerical simulations, highlighting its superior noise removal performance compared to traditional acoustic noise cancellation approaches.