metadata
language: vie
datasets:
- legacy-datasets/common_voice
- vlsp2020_vinai_100h
- AILAB-VNUHCM/vivos
- doof-ferb/vlsp2020_vinai_100h
- doof-ferb/fpt_fosd
- doof-ferb/infore1_25hours
- linhtran92/viet_bud500
- doof-ferb/LSVSC
- doof-ferb/vais1000
- doof-ferb/VietMed_labeled
- NhutP/VSV-1100
- doof-ferb/Speech-MASSIVE_vie
- doof-ferb/BibleMMS_vie
- capleaf/viVoice
metrics:
- wer
pipeline_tag: automatic-speech-recognition
tags:
- transcription
- audio
- speech
- chunkformer
- asr
- automatic-speech-recognition
license: cc-by-nc-4.0
model-index:
- name: ChunkFormer Large Vietnamese
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset:
name: common-voice-vietnamese
type: common_voice
args: vi
metrics:
- name: Test WER
type: wer
value: 6.66
source:
name: Common Voice Vi Leaderboard
url: >-
https://paperswithcode.com/sota/speech-recognition-on-common-voice-vi
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset:
name: VIVOS
type: vivos
args: vi
metrics:
- name: Test WER
type: wer
value: 4.18
source:
name: Vivos Leaderboard
url: https://paperswithcode.com/sota/speech-recognition-on-vivos
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset:
name: VLSP - Task 1
type: vlsp
args: vi
metrics:
- name: Test WER
type: wer
value: 14.09
ChunkFormer-Large-Vie: Large-Scale Pretrained ChunkFormer for Vietnamese Automatic Speech Recognition
Citation
If you use this work in your research, please cite:
@INPROCEEDINGS{10888640,
author={Le, Khanh and Ho, Tuan Vu and Tran, Dung and Chau, Duc Thanh},
booktitle={ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
title={ChunkFormer: Masked Chunking Conformer For Long-Form Speech Transcription},
year={2025},
volume={},
number={},
pages={1-5},
keywords={Scalability;Memory management;Graphics processing units;Signal processing;Performance gain;Hardware;Resource management;Speech processing;Standards;Context modeling;chunkformer;masked batch;long-form transcription},
doi={10.1109/ICASSP49660.2025.10888640}}
}
