THE FOSAFER SYSTEM FOR THE ICASSP2024 IN-CAR MULTI-CHANNEL AUTOMATIC SPEECH RECOGNITION CHALLENGE

被引：0

作者：

Huang, Shangkun ^{[1
]}

Du, Yuxuan ^{[1
]}

Wang, Yankai ^{[1
]}

Deng, Jing ^{[1
]}

Zheng, Rong ^{[1
]}

机构：

[1] Beijing Fosafer Informat Technol Co Ltd, Beijing, Peoples R China

来源：

2024 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING WORKSHOPS, ICASSPW 2024 | 2024年

关键词：

Robust automatic speech recognition; self-supervised learning representation; speech enhancement; speaker diarization;

D O I：

10.1109/ICASSPW62465.2024.10625781

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

This paper presents the Fosafer's submissions to the ICASSP 2024 In-Car Multi-Channel Automatic Speech Recognition Challenge (ICMC-ASR), which includes both the Automatic Speech Recognition (ASR) and Automatic Speech Diarization and Recognition (ASDR) systems. In Track1, a robust ASR system with data augmentation, self-supervised learning representation (SSLR), and speech enhancement (SE) achieved the second place. In Track2, different speaker diarization algorithms were fully exploited and achieved the fifth place.

引用

页码：5 / 6

页数：2

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