Datasets:
File size: 3,070 Bytes
e20f826 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 | # quest.py — for VoiceProfiler/QuEsT
# Keeps `text_quz` (Quechua) and `text_es` (Spanish), plus a unified `text` column for the viewer.
import os
import datasets
from datasets import load_dataset, Audio
class QuEsT(datasets.GeneratorBasedBuilder):
VERSION = datasets.Version("1.0.0")
BUILDER_CONFIGS = [
datasets.BuilderConfig(name="default", version=VERSION, description="Default configuration"),
]
DEFAULT_CONFIG_NAME = "default"
def _info(self):
return datasets.DatasetInfo(
description="Quechua–Spanish speech dataset (QuEsT) with aligned transcripts.",
features=datasets.Features({
"id": datasets.Value("string"),
"language": datasets.Value("string"),
"text": datasets.Value("string"),
"has_transcription": datasets.Value("bool"),
"audio": Audio(sampling_rate=None, mono=True),
}),
)
def _split_generators(self, dl_manager):
base = os.path.dirname(os.path.abspath(__file__))
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN,
gen_kwargs={"parquet_path": os.path.join(base, "data", "train.parquet")}),
datasets.SplitGenerator(name=datasets.Split.TEST,
gen_kwargs={"parquet_path": os.path.join(base, "data", "test.parquet")}),
]
def _generate_examples(self, parquet_path: str):
ds = load_dataset("parquet", data_files=parquet_path, split="train")
cols = set(ds.column_names)
length = len(ds)
# Normalize possible alternate column names
if "audio" in cols and "path" not in cols:
ds = ds.rename_column("audio", "path")
if "label" in cols and "text" not in cols:
ds = ds.rename_column("label", "text")
if "lang" in cols and "language" not in cols:
ds = ds.rename_column("lang", "language")
if "has_transcription" not in ds.column_names:
texts = ds["text"] if "text" in ds.column_names else [None] * length
default = [False if t in (None, "") else True for t in texts]
ds = ds.add_column("has_transcription", default)
# Ensure required columns exist
for c in ["id", "language", "text", "path", "has_transcription"]:
if c not in ds.column_names:
fill = [None] * length
if c == "has_transcription":
fill = [False] * length
ds = ds.add_column(c, fill)
# Cast to Audio() for playback in viewer
ds = ds.cast_column("path", Audio(sampling_rate=None, mono=True))
ds = ds.rename_column("path", "audio")
# Keep only desired columns (and in order)
keep = ["id", "language", "text", "has_transcription", "audio"]
drop = [c for c in ds.column_names if c not in keep]
if drop:
ds = ds.remove_columns(drop)
for i, ex in enumerate(ds):
yield i, ex
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