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Ph.D. Dissertation Defense - Hu Hu

Title:  Bayesian Adaptive Learning of Deep Latent Variables for Acoustic Knowledge Transfer

Committee:

Dr. Chin-Hui Lee, ECE, Chair, Advisor

Dr. David Anderson, ECE

Dr. Larry Heck, ECE

Dr. Elliot Moore, ECE

Dr. Sabato Marco Siniscalchi, U of Palermo

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Summary

This dissertation proposes a Bayesian adaptive learning framework that focuses on estimating a manageable number of latent variables. We explore both variational Bayesian (VB) and maximum a posteriori (MAP) estimation techniques within this framework. Experimental results on acoustic scene classification and spoken command recognition tasks demonstrate that our approach outperforms other knowledge transfer methods.

Details

Friday
Nov 8 2024
09:00am - 11:00am

Location: Room 5126, Centergy

In campus calendar: No

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  • Workflow status: Published
  • Created by: Daniela Staiculescu
  • Created: 11/07/2024
  • Modified By: Daniela Staiculescu
  • Modified: 11/07/2024

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