Noise Reduction and Speech Enhancement Using Wiener Filter
Objective
The primary objective of this project is to develop and implement a noise reduction and speech enhancement system based on the Wiener filter algorithm. The project aims to enhance the quality of audio recordings in noisy environments, making them clearer and more intelligible
Abstract
Using orthogonal frequency division multiplexing (OFDM), the digital data transmission rate can exceed 2.5 Tb/s. In the age of pandemics, digital voice enhancement is essential. This is a result of the vast majority of information and communication taking place online. Not everyone has a private space for digital conversation, though. As a result, during recording, background noise from the indoor environment may affect the speech. In areas where a quick denoising process is required, such as voice communication or voice identification, speech denoising has various advantages. This essay assesses the effectiveness of using Wiener filters to reduce noise. The enhancement of distorted speech by additive noise has been done, however it is still a difficult subject. To create noisy speech, we combine the noise with the example clean speech. For SNR 0 to 0.5dB with an increase of 0.01dB, noise levels are generated. To depict significant additive noise, we pick low SNR. To produce filtered noisy speech, we then apply Wiener Noise Reduction to the noisy speech. Finally, for each noise level, we compare the Mean Square Error (MSE) of the filtered speech to the original speech. The outcomes demonstrate a reduction in noise. Since the noisy bits have been muted, the non-speech portions now appear better. Our study demonstrates that the suggested method successfully enhances communication in a loud setting up to an order of.
Keywords: Speech Signals, Noise Reduction, Speech Enhancement and Wiener.
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
Block Diagram
Specifications
Software: Matlab 2020a or above
Hardware:
Operating Systems:
- Windows 10
- Windows 7 Service Pack 1
- Windows Server 2019
- Windows Server 2016
Processors:
Minimum: Any Intel or AMD x86-64 processor
Recommended: Any Intel or AMD x86-64 processor with four logical cores and AVX2 instruction set support
Disk:
Minimum: 2.9 GB of HDD space for MATLAB only, 5-8 GB for a typical installation
Recommended: An SSD is recommended A full installation of all MathWorks products may take up to 29 GB of disk space
RAM:
Minimum: 4 GB
Recommended: 8 GB
Learning Outcomes
· Introduction to Matlab
· What is EISPACK & LINPACK
· How to start with MATLAB
· About Matlab language
· Matlab coding skills
· About tools & libraries
· Application Program Interface in Matlab
· About Matlab desktop
· How to use Matlab editor to create M-Files
· Features of Matlab
· Basics on Matlab
· What is Signal Processing?
· About Signal Processing
· Introduction to Signal Processing
· How analog and digital signal is formed
· Importing the signal via signal acquisition tools
· Analyzing and manipulation of signals.
· Phases of signal processing:
· Acquisition
· Signal enhancement
· Signal restoration
· Medical Signal Processing
· Medical Signal Analysis
· Medical Signal Diagnosis
· Filtering techniques
· Machine Learning Algorithms
· Deep Learning Algorithms etc.
· How to extend our work to another real time applications
· Project development Skills
o Problem analyzing skills
o Problem solving skills
o Creativity and imaginary skills
o Programming skills
o Deployment
o Testing skills
o Debugging skills
o Project presentation skills
o Thesis writing skills
Paper Publishing
Request Call Back
Would you like to receive a free callback now?
Choose the best time for callback:
Leave your message and we will contact you as soon as possible
Disclaimer - Takeoff Edu Group Projects, are not associated or affiliated with IEEE, in any way. The IEEE Projects mentioned here are mentioned in the context of student projects, whose ideas are derived from IEEE publications, and not projects of or by IEEE.
