MER 2023: Multi-label Learning, Modality Robustness, and Semi-Supervised Learning

04/18/2023
by   Zheng Lian, et al.
0

Over the past few decades, multimodal emotion recognition has made remarkable progress with the development of deep learning. However, existing technologies are difficult to meet the demand for practical applications. To improve the robustness, we launch a Multimodal Emotion Recognition Challenge (MER 2023) to motivate global researchers to build innovative technologies that can further accelerate and foster research. For this year's challenge, we present three distinct sub-challenges: (1) MER-MULTI, in which participants recognize both discrete and dimensional emotions; (2) MER-NOISE, in which noise is added to test videos for modality robustness evaluation; (3) MER-SEMI, which provides large amounts of unlabeled samples for semi-supervised learning. In this paper, we test a variety of multimodal features and provide a competitive baseline for each sub-challenge. Our system achieves 77.57 mean squared error (MSE) for MER-MULTI, 69.82 for MER-NOISE, and 86.75 code is available at https://github.com/zeroQiaoba/MER2023-Baseline.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
09/05/2020

Semi-supervised Multi-modal Emotion Recognition with Cross-Modal Distribution Matching

Automatic emotion recognition is an active research topic with wide rang...
research
04/25/2017

Semi-supervised Bayesian Deep Multi-modal Emotion Recognition

In emotion recognition, it is difficult to recognize human's emotional s...
research
10/27/2022

Exploiting modality-invariant feature for robust multimodal emotion recognition with missing modalities

Multimodal emotion recognition leverages complementary information acros...
research
03/27/2023

EEGMatch: Learning with Incomplete Labels for Semi-Supervised EEG-based Cross-Subject Emotion Recognition

Electroencephalography (EEG) is an objective tool for emotion recognitio...
research
06/21/2022

Exploring the Effectiveness of Self-supervised Learning and Classifier Chains in Emotion Recognition of Nonverbal Vocalizations

We present an emotion recognition system for nonverbal vocalizations (NV...
research
10/28/2022

Leveraging Label Correlations in a Multi-label Setting: A Case Study in Emotion

Detecting emotions expressed in text has become critical to a range of f...
research
07/14/2022

Semi-supervised cross-lingual speech emotion recognition

Speech emotion recognition (SER) on a single language has achieved remar...

Please sign up or login with your details

Forgot password? Click here to reset