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Estimating the Uncertainty in Emotion Class Labels with
  Utterance-Specific Dirichlet Priors

Estimating the Uncertainty in Emotion Class Labels with Utterance-Specific Dirichlet Priors

8 March 2022
Wen Wu
Chuxu Zhang
Xixin Wu
P. Woodland
ArXivPDFHTML

Papers citing "Estimating the Uncertainty in Emotion Class Labels with Utterance-Specific Dirichlet Priors"

26 / 26 papers shown
Title
Bayesian WeakS-to-Strong from Text Classification to Generation
Bayesian WeakS-to-Strong from Text Classification to Generation
Ziyun Cui
Ziyang Zhang
Wen Wu
Wen Wu
Chao Zhang
66
3
0
24 May 2024
Fusion approaches for emotion recognition from speech using acoustic and
  text-based features
Fusion approaches for emotion recognition from speech using acoustic and text-based features
L. Pepino
Pablo Riera
Luciana Ferrer
Agustin Gravano
58
49
0
27 Mar 2024
Group Gated Fusion on Attention-based Bidirectional Alignment for
  Multimodal Emotion Recognition
Group Gated Fusion on Attention-based Bidirectional Alignment for Multimodal Emotion Recognition
Pengfei Liu
Kun Li
Helen Meng
CVBM
63
42
0
17 Jan 2022
Multimodal Emotion Recognition with High-level Speech and Text Features
Multimodal Emotion Recognition with High-level Speech and Text Features
M. R. Makiuchi
Kuniaki Uto
Koichi Shinoda
31
72
0
29 Sep 2021
CopyPaste: An Augmentation Method for Speech Emotion Recognition
CopyPaste: An Augmentation Method for Speech Emotion Recognition
R. Pappagari
Jesús Villalba
Piotr Żelasko
Laureano Moro-Velazquez
Najim Dehak
38
40
0
27 Oct 2020
Emotion recognition by fusing time synchronous and time asynchronous
  representations
Emotion recognition by fusing time synchronous and time asynchronous representations
Wen Wu
Chao Zhang
P. Woodland
44
67
0
27 Oct 2020
x-vectors meet emotions: A study on dependencies between emotion and
  speaker recognition
x-vectors meet emotions: A study on dependencies between emotion and speaker recognition
R. Pappagari
Tianzi Wang
Jesus Villalba
Nanxin Chen
Najim Dehak
57
108
0
12 Feb 2020
Reverse KL-Divergence Training of Prior Networks: Improved Uncertainty
  and Adversarial Robustness
Reverse KL-Divergence Training of Prior Networks: Improved Uncertainty and Adversarial Robustness
A. Malinin
Mark Gales
UQCV
AAML
56
174
0
31 May 2019
Speaker diarisation using 2D self-attentive combination of embeddings
Speaker diarisation using 2D self-attentive combination of embeddings
Guangzhi Sun
Chao Zhang
P. Woodland
42
31
0
08 Feb 2019
Why ReLU networks yield high-confidence predictions far away from the
  training data and how to mitigate the problem
Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem
Matthias Hein
Maksym Andriushchenko
Julian Bitterwolf
OODD
140
556
0
13 Dec 2018
BERT: Pre-training of Deep Bidirectional Transformers for Language
  Understanding
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Jacob Devlin
Ming-Wei Chang
Kenton Lee
Kristina Toutanova
VLM
SSL
SSeg
1.1K
93,936
0
11 Oct 2018
MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in
  Conversations
MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations
Soujanya Poria
Devamanyu Hazarika
Navonil Majumder
Gautam Naik
Min Zhang
Rada Mihalcea
85
1,055
0
05 Oct 2018
Emotion Recognition in Speech using Cross-Modal Transfer in the Wild
Emotion Recognition in Speech using Cross-Modal Transfer in the Wild
Samuel Albanie
Arsha Nagrani
Andrea Vedaldi
Andrew Zisserman
CVBM
53
271
0
16 Aug 2018
Multimodal Sentiment Analysis using Hierarchical Fusion with Context
  Modeling
Multimodal Sentiment Analysis using Hierarchical Fusion with Context Modeling
Navonil Majumder
Devamanyu Hazarika
Alexander Gelbukh
Min Zhang
Soujanya Poria
38
321
0
16 Jun 2018
Multi-Modal Emotion recognition on IEMOCAP Dataset using Deep Learning
Multi-Modal Emotion recognition on IEMOCAP Dataset using Deep Learning
Samarth Tripathi
Sarthak Tripathi
Homayoon Beigi
41
147
0
16 Apr 2018
Multimodal Sentiment Analysis: Addressing Key Issues and Setting up the
  Baselines
Multimodal Sentiment Analysis: Addressing Key Issues and Setting up the Baselines
Soujanya Poria
Navonil Majumder
Devamanyu Hazarika
Min Zhang
Alexander Gelbukh
Amir Hussain
20
173
0
19 Mar 2018
Predictive Uncertainty Estimation via Prior Networks
Predictive Uncertainty Estimation via Prior Networks
A. Malinin
Mark Gales
UD
BDL
EDL
UQCV
PER
179
907
0
28 Feb 2018
Improved TDNNs using Deep Kernels and Frequency Dependent Grid-RNNs
Improved TDNNs using Deep Kernels and Frequency Dependent Grid-RNNs
Florian Kreyssig
Chuxu Zhang
P. Woodland
37
23
0
18 Feb 2018
Training Confidence-calibrated Classifiers for Detecting
  Out-of-Distribution Samples
Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples
Kimin Lee
Honglak Lee
Kibok Lee
Jinwoo Shin
OODD
105
880
0
26 Nov 2017
End-to-End Multimodal Emotion Recognition using Deep Neural Networks
End-to-End Multimodal Emotion Recognition using Deep Neural Networks
Panagiotis Tzirakis
George Trigeorgis
M. Nicolaou
Björn Schuller
Stefanos Zafeiriou
HAI
35
542
0
27 Apr 2017
SphereFace: Deep Hypersphere Embedding for Face Recognition
SphereFace: Deep Hypersphere Embedding for Face Recognition
Weiyang Liu
Yandong Wen
Zhiding Yu
Ming Li
Bhiksha Raj
Le Song
CVBM
222
2,790
0
26 Apr 2017
A Structured Self-attentive Sentence Embedding
A Structured Self-attentive Sentence Embedding
Zhouhan Lin
Minwei Feng
Cicero Nogueira dos Santos
Mo Yu
Bing Xiang
Bowen Zhou
Yoshua Bengio
110
2,132
0
09 Mar 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
548
5,748
0
05 Dec 2016
Rethinking the Inception Architecture for Computer Vision
Rethinking the Inception Architecture for Computer Vision
Christian Szegedy
Vincent Vanhoucke
Sergey Ioffe
Jonathon Shlens
Z. Wojna
3DV
BDL
564
27,231
0
02 Dec 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
533
9,233
0
06 Jun 2015
Deep Neural Networks are Easily Fooled: High Confidence Predictions for
  Unrecognizable Images
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images
Anh Totti Nguyen
J. Yosinski
Jeff Clune
AAML
141
3,261
0
05 Dec 2014
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