A Review on Finding Efficient Approach to Detect Customer Emotion Analysis using Deep Learning Analysis
Volume-3 | Issue-2
A Comparative Analysis of Prediction of Student Results Using Decision Trees and Random Forest
Volume-4 | Issue-3
A Review on Microstrip Patch Antenna Performance Improvement Techniques on Various Applications
Volume-3 | Issue-3
Study of Security Mechanisms to Create a Secure Cloud in a Virtual Environment with the Support of Cloud Service Providers
Volume-2 | Issue-3
Construction of Black Box to Detect the Location of Road Mishap in Remote Area in the IoT Domain
Volume-3 | Issue-2
Fault Diagnosis in Hybrid Renewable Energy Sources with Machine Learning Approach
Volume-3 | Issue-3
Secure and Optimized Cloud-Based Cyber-Physical Systems with Memory-Aware Scheduling Scheme
Volume-2 | Issue-3
Computer Vision on IOT Based Patient Preference Management System
Volume-2 | Issue-2
Stochastic Geometry and Performance Analysis of Large Scale Wireless Networks
Volume-3 | Issue-3
ENHANCED NETWORK PERFORMANCE AND MOBILITY MANAGEMENT OF IOT MULTI NETWORKS
Volume-1 | Issue-2
Fake News Detection using Data Mining Techniques
Volume-3 | Issue-4
A Comparative Analysis of Prediction of Student Results Using Decision Trees and Random Forest
Volume-4 | Issue-3
A Review on Microstrip Patch Antenna Performance Improvement Techniques on Various Applications
Volume-3 | Issue-3
Speedy Detection Module for Abandoned Belongings in Airport Using Improved Image Processing Technique
Volume-3 | Issue-4
Deployment of Artificial Intelligence with Bootstrapped Meta-Learning in Cyber Security
Volume-4 | Issue-3
Design an Early Detection and Classification for Diabetic Retinopathy by Deep Feature Extraction based Convolution Neural Network
Volume-3 | Issue-2
Design of an Intelligent Approach on Capsule Networks to Detect Forged Images
Volume-3 | Issue-3
SDN Controller and Blockchain to Secure Information Transaction in a Cluster Structure
Volume-3 | Issue-2
A Review on Finding Efficient Approach to Detect Customer Emotion Analysis using Deep Learning Analysis
Volume-3 | Issue-2
Future Challenges of the Internet of Things in the Health Care Domain - An Overview
Volume-3 | Issue-4
Volume - 3 | Issue - 4 | december 2021
Published
11 May, 2022
Acoustic signal classification issues are addressed in this work using spectral examination, channel extracting the features from the input and machine learning algorithm. This brief article examines the effect of various settings on feature extraction. This feature-level channel combination's accuracy increase is then observed. To categorise things, pattern recognition utilises a variety of classification schemes. "Pattern" refers to the measures that must be categorised with accurate feature extracted. Images and audio signals are among the most common kinds of measurements. The proposed Support Vector Machine (SVM) is used for the necessity of an effective categorization of acoustic signals driven by the continual improvements in multimedia technology. This study uses two machine learning algorithms to enhance audio classification and categorization. The proposed SVM achieves superior performance than the other ML algorithm by spectral features.
KeywordsMachine Learning (ML) spectral analysis SVM audio classification Spectral Centroid feature
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