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CopyPaste: An Augmentation Method for Speech Emotion Recognition
v1v2 (latest)

CopyPaste: An Augmentation Method for Speech Emotion Recognition

IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2020
27 October 2020
R. Pappagari
Jesús Villalba
Piotr Żelasko
Laureano Moro-Velazquez
Najim Dehak
ArXiv (abs)PDFHTML

Papers citing "CopyPaste: An Augmentation Method for Speech Emotion Recognition"

12 / 12 papers shown
Learning Emotion-Invariant Speaker Representations for Speaker Verification
Learning Emotion-Invariant Speaker Representations for Speaker VerificationIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2024
Jingguang Tian
Xinhui Hu
Xinkang Xu
291
6
0
24 May 2025
Designing and Evaluating Speech Emotion Recognition Systems: A reality
  check case study with IEMOCAP
Designing and Evaluating Speech Emotion Recognition Systems: A reality check case study with IEMOCAPIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2023
Nikolaos Antoniou
Athanasios Katsamanis
Theodoros Giannakopoulos
Shrikanth Narayanan
174
24
0
03 Apr 2023
EdgeYOLO: An Edge-Real-Time Object Detector
EdgeYOLO: An Edge-Real-Time Object DetectorCybersecurity and Cyberforensics Conference (CC), 2023
Shihan Liu
Junli Zha
Jian Sun
Zhuoao Li
G. Wang
ObjD
170
68
0
15 Feb 2023
Improving Speech Emotion Recognition with Unsupervised Speaking Style
  Transfer
Improving Speech Emotion Recognition with Unsupervised Speaking Style TransferIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2022
Leyuan Qu
Wei Wang
C. Weber
F. Ren
Taiha Li
S. Wermter
217
4
0
16 Nov 2022
Is Style All You Need? Dependencies Between Emotion and GST-based
  Speaker Recognition
Is Style All You Need? Dependencies Between Emotion and GST-based Speaker Recognition
Morgan Sandler
Arun Ross
154
0
0
15 Nov 2022
A Comparative Study of Data Augmentation Techniques for Deep Learning
  Based Emotion Recognition
A Comparative Study of Data Augmentation Techniques for Deep Learning Based Emotion Recognition
Ravi Shankar
Abdouh Harouna Kenfack
Arjun Somayazulu
A. Venkataraman
112
5
0
09 Nov 2022
Non-Contrastive Self-supervised Learning for Utterance-Level Information
  Extraction from Speech
Non-Contrastive Self-supervised Learning for Utterance-Level Information Extraction from SpeechIEEE Journal on Selected Topics in Signal Processing (IEEE JSTSP), 2022
Jaejin Cho
Jesús Villalba
Laureano Moro-Velazquez
Najim Dehak
SSL
204
22
0
10 Aug 2022
Dawn of the transformer era in speech emotion recognition: closing the
  valence gap
Dawn of the transformer era in speech emotion recognition: closing the valence gapIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022
Johannes Wagner
Andreas Triantafyllopoulos
H. Wierstorf
Maximilian Schmitt
Felix Burkhardt
F. Eyben
Björn W. Schuller
389
409
0
14 Mar 2022
Estimating the Uncertainty in Emotion Class Labels with
  Utterance-Specific Dirichlet Priors
Estimating the Uncertainty in Emotion Class Labels with Utterance-Specific Dirichlet PriorsIEEE Transactions on Affective Computing (IEEE TAC), 2022
Wen Wu
Chuxu Zhang
Xixin Wu
P. Woodland
294
17
0
08 Mar 2022
Privacy-preserving Speech Emotion Recognition through Semi-Supervised
  Federated Learning
Privacy-preserving Speech Emotion Recognition through Semi-Supervised Federated Learning
Vasileios Tsouvalas
T. Ozcelebi
N. Meratnia
146
33
0
05 Feb 2022
Beyond Isolated Utterances: Conversational Emotion Recognition
Beyond Isolated Utterances: Conversational Emotion Recognition
R. Pappagari
Piotr Żelasko
Jesús Villalba
Laureano Moro-Velazquez
Najim Dehak
176
5
0
13 Sep 2021
Best Practices for Noise-Based Augmentation to Improve the Performance
  of Deployable Speech-Based Emotion Recognition Systems
Best Practices for Noise-Based Augmentation to Improve the Performance of Deployable Speech-Based Emotion Recognition Systems
Mimansa Jaiswal
E. Provost
108
0
0
18 Apr 2021
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