Sentiment Analysis And Speaker Mapping with Machine Learning

Author(s)	Mr. Mayur Ankushrao, Mr. Vishal Mule, Mr. Aniket Markad, Mr. Sanket Pawar
Country	India
Abstract	In an automated environment when multiple user is interacting with automated system, identification for each one and their sentiment recognition is fundamental for real-time emotion understanding, which is needed in personal and efficient response generation. This work aims at an integrated machine learning architecture that integrates speaker identification and sentiment analysis to realize precise and user-specific emotion recognition. It utilizes Mel Frequency Cepstral Coefficients (MFCC) and Dynamic Time Warping (DTW) as reliable speaker mapping method and applies Support Vector Machine (SVM), Naive Bayes, and Variance-Aware Network Decomposition and Regularization (VADER) for sentiment classification from both the acoustic feature and the text transcript. Performance evaluation has shown strong performance. It ensures that end-user will be receiving practical insights and delicate feelings about a person and that this kind of understanding will also be of service in domains of customer service analytics, education, healthcare monitoring, and recommendation systems.
Keywords	Sentiment, Speaker, User, Mapping, Video, Emotion, Audio
Field	Engineering
Published In	Volume 16, Issue 4, October-December 2025
Published On	2025-11-15
DOI	https://doi.org/10.71097/IJSAT.v16.i4.9418
Short DOI	https://doi.org/hbbmz2

About IJSAT Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us	Message on WhatsApp	+91-9687-182-185	editor@ijsat.org

International Journal on Science and Technology