A Novel Reconfigurable Hardware Design for Speech Enhancement Based on Multi-Band Spectral Subtraction Involving Magnitude and Phase Components

TL;DR

This paper introduces a reconfigurable FPGA-based hardware design for speech enhancement using multi-band spectral subtraction that leverages both magnitude and phase components, achieving improved noise reduction and throughput.

Contribution

It presents a novel multi-band spectral subtraction method involving magnitude and phase, implemented on FPGA, and the first hardware realization for speech enhancement of this kind.

Findings

Achieved better SNR compared to existing methods.

Implemented on Spartan6 FPGA with detailed resource analysis.

Demonstrated high throughput through parallel processing.

Abstract

This paper proposes an efficient reconfigurable hardware design for speech enhancement based on multi band spectral subtraction algorithm and involving both magnitude and phase components. Our proposed design is novel as it estimates environmental noise from speech adaptively utilizing both magnitude and phase components of the speech spectrum. We performed multi-band spectrum subtraction by dividing the noisy speech spectrum into different non-uniform frequency bands having varying signal to noise ratio (SNR) and subtracting the estimated noise from each of these frequency bands. This results to the elimination of noise from both high SNR and low SNR signal components for all the frequency bands. We have coined our proposed speech enhancement technique as Multi Band Magnitude Phase Spectral Subtraction (MBMPSS). The magnitude and phase operations are executed concurrently exploiting the parallel logic blocks of Field Programmable Gate Array (FPGA), thus increasing the throughput of the system to a great extent. We have implemented our design on Spartan6 Lx45 FPGA and presented the implementation result in terms of resource utilization and delay information for the different blocks of our design. To the best of our best knowledge, this is a new type of hardware design for speech enhancement application and also a first of its kind implementation on reconfigurable hardware. We have used benchmark audio data for the evaluation of the proposed hardware and the experimental results show that our hardware shows a better SNR value compared to the existing state of the art research works.