Paper Info
Title
LSSED: A LARGE-SCALE DATASET AND BENCHMARK FOR SPEECH EMOTION RECOGNITION
Abstract
Speech emotion recognition is a vital contributor to the next generation of human-computer interaction (HCI). However, current existing small-scale databases have limited the development of related research. In this paper, we present LSSED, a challenging large-scale english speech emotion dataset, which has data collected from 820 subjects to simulate realworld distribution. In addition, we release some pre-trained models based on LSSED, which can not only promote the development of speech emotion recognition, but can also be transferred to related downstream tasks such as mental health analysis where data is extremely difficult to collect. Finally, our experiments show the necessity of large-scale datasets and the effectiveness of pre-trained models. The dateset will be released on https://github.com/tobefans/LSSED.
Year
DOI
Venue
2021
10.1109/ICASSP39728.2021.9414542
2021 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP 2021)
Keywords
DocType
Citations 
speech emotion recognition, dataset, pretrained model, deep learning
Conference
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Weiquan Fan132.08
Xiangmin Xu210017.62
Xiaofen Xing3246.79
Weidong Chen400.68
Dong-Yan Huang59218.60