Not All Features are Equal: Selection of Robust Features for Speech Emotion Recognition in Noisy Environments-Reference-Cited by-同舟云学术

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Not All Features are Equal: Selection of Robust Features for Speech Emotion Recognition in Noisy Environments

Published:2022-05-23 Issue: Volume: Page:
ISSN:
Container-title:ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Leem Seong-Gyun¹,Fulford Daniel²,Onnela Jukka-Pekka³,Gard David¹,Busso Carlos¹

Affiliation:

1. The University of Texas at Dallas,Department of Electrical and Computer Engineering

2. Boston University,Occupational Therapy and Psychological & Brain Sciences

3. Harvard University,Department of Biostatistics, Harvard T.H. Chan School of Public Health

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9745891/9746004/09747705.pdf?arnumber=9747705

Reference19 articles.

1. From neural PCA to deep unsupervised learning

2. Semi-Supervised Speech Emotion Recognition With Ladder Networks

3. Ladder Networks for Emotion Recognition: Using Unsupervised Auxiliary Tasks to Improve Predictions of Emotional Attributes

4. Emotion recognition in the noise applying large acoustic feature sets;schuller;ISCA Speech Prosody,2006

5. An Unsupervised frame Selection Technique for Robust Emotion Recognition in Noisy Speech

Cited by 9 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. TRNet: Two-level Refinement Network leveraging speech enhancement for noise robust speech emotion recognition;Applied Acoustics;2024-11

2. Speech Emotion Recognition under Noisy Environments with SNR Down to −6 dB Using Multi-Decoder Wave-U-Net;Applied Sciences;2024-06-17

3. A review on speech emotion recognition: A survey, recent advances, challenges, and the influence of noise;Neurocomputing;2024-02

4. Selective Acoustic Feature Enhancement for Speech Emotion Recognition With Noisy Speech;IEEE/ACM Transactions on Audio, Speech, and Language Processing;2024

5. An Engineering View on Emotions and Speech: From Analysis and Predictive Models to Responsible Human-Centered Applications;Proceedings of the IEEE;2023-10

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