A Method for Voice Activity Detection using K-Means Clustering-Reference-Cited by-同舟云学术

A Method for Voice Activity Detection using K-Means Clustering

Published:2022-10-03 Issue: Volume: Page:
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Container-title:2022 13th International Conference on Computing Communication and Networking Technologies (ICCCNT)
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Author:

Agarwal Atul Rohit¹,Tiwari Sourabh²,Patage Vinay Vasanth²,Ganesh S Sankar³,S Sudhakar M³

Affiliation:

1. Vellore Institute of Technology,School of Computer Science Engineering,Vellore,India

2. Samsung R&D Institute,Voice Enabling Group,Bangalore,India

3. Vellore Institute of Technology,Department of Communication Engineering,Vellore,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9984157/9984211/09984425.pdf?arnumber=9984425

Reference19 articles.

1. Polyphonic Sound Event Detection and Classification using Convolutional Recurrent Neural Network with Mean Teacher

2. A Faster Approach For Direct Speech to Speech Translation

3. Feature Genuinization based Residual Squeeze-and-Excitation for Audio Anti-Spoofing in Sound AI

4. Sound Event Separation and Classification in Domestic Environment using Mean Teacher

5. Gender and Age Group Predictions from Speech Features using Multi-Layer Perceptron Model;goyal;2020 IEEE 17th India Council International Conference (INDICON),2020

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1. Public Human Assault Prediction Using Human Activity Recognition with AI;2024 International Conference on Advances in Data Engineering and Intelligent Computing Systems (ADICS);2024-04-18

2. The Evolution of Voice Assistants: From Text-to-Speech to Conversational AI;2024 2nd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT);2024-01-04

3. Active Speaker Detection Using Audio, Visual, and Depth Modalities: A Survey;IEEE Access;2024

4. Voice Activity Detection Using Convolutional Recurrent Neural Networks;Proceedings of the Future Technologies Conference (FTC) 2023, Volume 2;2023