4 papers
A Comprehensive Study on the Effectiveness of ASR Representations for Noise-Robust Speech Emotion Recognition
Xiaohan Shi, Jiajun He, Xingfeng Li +1
This paper proposes an efficient attempt to noisy speech emotion recognition (NSER). Conventional NSER approaches have proven effective in mitigating the impact of artificial noise…
EM2LDL: A Multilingual Speech Corpus for Mixed Emotion Recognition through Label Distribution Learning
Xingfeng Li, Xiaohan Shi, Junjie Li +4
This study introduces EM2LDL, a novel multilingual speech corpus designed to advance mixed emotion recognition through label distribution learning. Addressing the limitations of pr…
M4SER: Multimodal, Multirepresentation, Multitask, and Multistrategy Learning for Speech Emotion Recognition
Jiajun He, Xiaohan Shi, Cheng-Hung Hu +3
Multimodal speech emotion recognition (SER) has emerged as pivotal for improving human-machine interaction. Researchers are increasingly leveraging both speech and textual informat…
Two-stage Framework for Robust Speech Emotion Recognition Using Target Speaker Extraction in Human Speech Noise Conditions
Jinyi Mi, Xiaohan Shi, Ding Ma +3
Developing a robust speech emotion recognition (SER) system in noisy conditions faces challenges posed by different noise properties. Most previous studies have not considered the…