ICASSP 2023accepted0 citations
The XMU System for Audio-Visual Diarization and Recognition in MISP Challenge 2022
Tao Li, Haodong Zhou, Jie Wang, Qingyang Hong, Lin Li
Abstract
In this paper, we present our work in track 2 of the Multi-modal Information based Speech Processing (MISP) 2022 Challenge. We built a cascaded system and explored different acoustic front-ends and end-to-end speech recognition back-ends based on multimodal. To promote effective fusion between the different modalities, we introduced a multi-level feature fusion network. By utilizing several additional strategies, our system achieved 31.88% in the concatenated minimum permutation character error rate (cpCER) on the evaluation set, achieving the 3th place ranking in the competition.
BibTeX
@inproceedings{icassp2023_thexmusystemfora,
title = {The XMU System for Audio-Visual Diarization and Recognition in MISP Challenge 2022},
author = {Tao Li and Haodong Zhou and Jie Wang and Qingyang Hong and Lin Li},
booktitle = {ICASSP 2023},
year = {2023}
}