1. Home
  2. Premium
  3. IEEE ICASSP 2020 Virtual Conference May 2020
  4. Multi-Conditioning And Data Augmentation Using Generative Noise Model For Speech Emotion Recognition In Noisy Conditions
  5. Multi-Conditioning And Data Augmentation Using Generative Noise Model For Speech Emotion Recognition In Noisy Conditions
Multi-Conditioning And Data Augmentation Using Generative Noise Model For Speech Emotion Recognition In Noisy Conditions

This video program is a part of the Premium package:

Multi-Conditioning And Data Augmentation Using Generative Noise Model For Speech Emotion Recognition In Noisy Conditions

  • IEEE MemberUS $11.00
  • Society MemberUS $0.00
  • IEEE Student MemberUS $11.00
  • Non-IEEE MemberUS $15.00
Purchase

Multi-Conditioning And Data Augmentation Using Generative Noise Model For Speech Emotion Recognition In Noisy Conditions

0 views
  • Share
Create Account or Sign In to post comments
Degradation due to additive noise is a significant road block in the real-life deployment of Speech Emotion Recognition (SER) systems. Most of the previous work in this field dealt with the noise degradation either at the signal or at the feature level. I
Degradation due to additive noise is a significant road block in the real-life deployment of Speech Emotion Recognition (SER) systems. Most of the previous work in this field dealt with the noise degradation either at the signal or at the feature level. I

Next Up

00:10:00
Anti-Jamming Routing For Internet Of Satellites: A Reinforcement Learning Approach
>
00:10:00
TEST
>
00:10:00
TEST #2
>
00:11:17
Article Production Process: Author Gateway and POPP - PoE 2020
>
00:05:01
Article Production Process: Service Levels & Workflow Options - PoE 2020
>
00:28:33
AWS Partner Solution Showcase presented by Scott Francis IoT Partner Solutions Architect at Amazon Web Services
>