metadata
configs:
- config_name: vi
data_files:
- split: train
path: corpus/vi.train.clean.jsonl
- split: eval
path: corpus/vi.eval.clean.jsonl
- config_name: vi-5000h
data_files:
- split: train
path: corpus/vi.train.coverage-5000h.jsonl
- split: eval
path: corpus/vi.eval.clean.jsonl
- config_name: audio-google_fleurs__vi_vn
data_files:
- split: train
path: audio/google_fleurs__vi_vn/*/part-*.parquet
- config_name: audio-leduckhai_multimed__vietnamese
data_files:
- split: train
path: audio/leduckhai_multimed__vietnamese/*/part-*.parquet
- config_name: audio-linhtran92__viet_bud500
data_files:
- split: train
path: audio/linhtran92__viet_bud500/*/part-*.parquet
- config_name: audio-tensorxt_vimedcss__default
data_files:
- split: train
path: audio/tensorxt_vimedcss__default/*/part-*.parquet
- config_name: audio-vietnamese_punctuated_jsonl__disco_eth_worldspeech
data_files:
- split: train
path: >-
audio/vietnamese_punctuated_jsonl__disco_eth_worldspeech/*/part-*.parquet
- config_name: audio-vietnamese_punctuated_jsonl__lemas_project_lemas_dataset_train
data_files:
- split: train
path: >-
audio/vietnamese_punctuated_jsonl__lemas_project_lemas_dataset_train/*/part-*.parquet
- config_name: audio-vietnamese_punctuated_jsonl__nhutp_vietspeech
data_files:
- split: train
path: audio/vietnamese_punctuated_jsonl__nhutp_vietspeech/*/part-*.parquet
- config_name: audio-vietnamese_speech_metadata__speechcolab_gigaspeech2
data_files:
- split: train
path: >-
audio/vietnamese_speech_metadata__speechcolab_gigaspeech2/*/part-*.parquet
vi cleaned speech corpus
This refresh provides a converged full train manifest, a frozen eval manifest, and a token-coverage subset of approximately 5000 hours. The validated FLAC payloads are reused without decoding or transcoding. Completely referenced Parquet shards are hard-linked locally; partial shards are filtered into exact row-only Parquet files.
Corpus overview
| Variant | Rows | Hours |
|---|---|---|
| train | 11,017,247 | 12483.122 |
| coverage_5000h | 4,166,867 | 5000.000 |
| eval | 1,476 | 1.998 |
All audio locators are portable and have the form
audio/<subset>/<group>/part-N.parquet#row=N.
The release audit records exact input/output hashes, rejected audio mappings, language-tag validation, and zero train/eval audio-identity overlap.
from datasets import load_dataset
ds = load_dataset("YuKuanFu/vi", "vi-5000h", split="train")