ENHANCEMENT AND NOISE REMOVING FROM SPEECH USING EMPIRICAL MODE DECOMPOSITION
Objective
The objective is to reduce noise in speech using Empirical Mode Decomposition (EMD). Noisy speech with varying signal-to-noise ratios (SNR) undergoes EMD, resulting in lower noise and improved Mean Square Error (MSE).
Abstract
We mix the noise with the clean sample speech to produce noisy speech. There is a rise of 0.01dB and noise levels of SNR 0 to 0.5dB. We select low SNR in order to depict large additive noise. We next subject the loud speech to EMD Noise Reduction in order to produce decreased noisy speech. Lastly, we compare the Mean Square Error (MSE) between the original and reconstructed speech for each noise level. The results show a decrease in noise. The non-speech parts now sound better because the loud parts have been hushed. Our results show that the recommended approach effectively improves communication in a noisy. We blend the clean sample speech with the noise to produce noisy speech. Noise levels range from SNR 0 to 0.5dB, with a 0.01dB increase. We select a low SNR to represent large additive noise. The noisy speech is then subjected to EMD Noise Reduction in order to produce decreased noisy speech. The Mean Square Error (MSE) between the original and reconstructed speech is then compared for each noise level. The results show that there is less noise. The quieter sections now sound better because the louder ones have been muffled. According to our research, the recommended approach effectively improves communication in a loud.
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
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