Vietnamese speech dataset
Collection
for any speech-related tasks including but not limited to: speech-to-text & text-to-speech, speech classification, speaker verification, etc. • 31 items • Updated • 43
audio audioduration (s) 0.1 29.2 | Metadata ID stringclasses 672
values |
|---|---|
VietMed_un_418 | |
VietMed_un_500 | |
VietMed_un_361 | |
VietMed_un_424 | |
VietMed_un_412 | |
VietMed_un_261 | |
VietMed_un_243 | |
VietMed_un_557 | |
VietMed_un_394 | |
VietMed_un_492 | |
VietMed_un_454 | |
VietMed_un_437 | |
VietMed_un_687 | |
VietMed_un_270 | |
VietMed_un_337 | |
VietMed_un_290 | |
VietMed_un_337 | |
VietMed_un_772 | |
VietMed_un_239 | |
VietMed_un_473 | |
VietMed_un_329 | |
VietMed_un_413 | |
VietMed_un_396 | |
VietMed_un_415 | |
VietMed_un_104 | |
VietMed_un_421 | |
VietMed_un_509 | |
VietMed_un_500 | |
VietMed_un_488 | |
VietMed_un_483 | |
VietMed_un_345 | |
VietMed_un_013 | |
VietMed_un_419 | |
VietMed_un_309 | |
VietMed_un_384 | |
VietMed_un_695 | |
VietMed_un_323 | |
VietMed_un_588 | |
VietMed_un_399 | |
VietMed_un_322 | |
VietMed_un_325 | |
VietMed_un_797 | |
VietMed_un_595 | |
VietMed_un_573 | |
VietMed_un_422 | |
VietMed_un_370 | |
VietMed_un_420 | |
VietMed_un_100 | |
VietMed_un_407 | |
VietMed_un_284 | |
VietMed_un_388 | |
VietMed_un_448 | |
VietMed_un_432 | |
VietMed_un_315 | |
VietMed_un_104 | |
VietMed_un_264 | |
VietMed_un_421 | |
VietMed_un_339 | |
VietMed_un_330 | |
VietMed_un_212 | |
VietMed_un_500 | |
VietMed_un_275 | |
VietMed_un_360 | |
VietMed_un_790 | |
VietMed_un_318 | |
VietMed_un_576 | |
VietMed_un_263 | |
VietMed_un_735 | |
VietMed_un_308 | |
VietMed_un_354 | |
VietMed_un_603 | |
VietMed_un_259 | |
VietMed_un_437 | |
VietMed_un_388 | |
VietMed_un_019 | |
VietMed_un_569 | |
VietMed_un_488 | |
VietMed_un_459 | |
VietMed_un_337 | |
VietMed_un_262 | |
VietMed_un_478 | |
VietMed_un_341 | |
VietMed_un_709 | |
VietMed_un_280 | |
VietMed_un_398 | |
VietMed_un_429 | |
VietMed_un_324 | |
VietMed_un_511 | |
VietMed_un_394 | |
VietMed_un_223 | |
VietMed_un_352 | |
VietMed_un_321 | |
VietMed_un_377 | |
VietMed_un_461 | |
VietMed_un_482 | |
VietMed_un_689 | |
VietMed_un_234 | |
VietMed_un_408 | |
VietMed_un_493 | |
VietMed_un_346 |
official announcement: https://arxiv.org/abs/2404.05659
official download: https://huggingface.co/datasets/leduckhai/VietMed
this repo contains the unlabeled set: 966h - 230k samples
i also gather the metadata: see info.csv
my extraction code: https://github.com/phineas-pta/fine-tune-whisper-vi/blob/main/misc/vietmed-unlabeled.py
need to do: check misspelling, restore foreign words phonetised to vietnamese
usage with HuggingFace:
# pip install -q "datasets[audio]"
from datasets import load_dataset
from huggingface_hub import hf_hub_download
from pandas import read_csv
repo_id = "doof-ferb/VietMed_unlabeled"
dataset = load_dataset(repo_id, split="train", streaming=True)
info_file = hf_hub_download(repo_id=repo_id, filename="info.csv", repo_type="dataset")
info_dict = read_csv(info_file, index_col=0).to_dict("index")
def merge_info(batch):
meta = info_dict.get(batch["Metadata ID"], "")
if meta != "":
batch["Domain"] = meta["Domain"]
batch["ICD-10 Code"] = meta["ICD-10 Code"]
batch["Accent"] = meta["Accent"]
else:
batch["Domain"] = ""
batch["ICD-10 Code"] = ""
batch["Accent"] = ""
return batch
dataset = dataset.map(merge_info)