ENHANCING SPEECH QUALITY IN NOISY ENVIRONMENTS USING FILTERING TECHNIQUES
Objective
To improve speech signal quality by reducing background noise using techniques like Spectral Subtraction and Wiener filtering, focusing on enhancing Mean Square Error (MSE) and Signal-to-Noise Ratio (SNR).
Abstract
Speech quality is affected by background noise in the real-time speech signal that is received. In order to improve voice signal quality and intelligibility, noise must be reduced or eliminated. Speech denoising has several applications, such as speech recognition and communication, where quick denoising is required. This study examines the efficacy of various noise reduction methods, such as Spectral Subtraction, Wiener filtering, in improving speech quality. The findings show that while lowering noise and enhancing clarity, each strategy has unique advantages and disadvantages. The techniques are most useful and difficult in low SNR settings, when they are applied to eliminate a variety of noises, such as noise from washing machines, noise from electric fans and traffic, finally leading to clear communication. According to the study, combining these strategies could improve performance even further. This strategy will concentrate on combining these methods to enhance the Mean Square Error (MSE) and Signal-to-Noise Ratio (SNR), producing even better outcomes in difficult acoustic circumstances.
Keywords: Speech Signals, Noise Reduction, Speech Enhancement, Mean Square Error (MSE), Signal-to-Noise Ratio (SNR) 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
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