|
from pathlib import Path |
|
from typing import List |
|
|
|
import datasets |
|
|
|
from seacrowd.utils import schemas |
|
from seacrowd.utils.configs import SEACrowdConfig |
|
from seacrowd.utils.constants import Licenses, Tasks |
|
|
|
_CITATION = """\ |
|
@misc{magichubLEXIndoIndonesian, |
|
author = {}, |
|
title = {LEX-INDO: AN INDONESIAN LEXICON}, |
|
year = {}, |
|
howpublished = {Online}, |
|
url = {https://magichub.com/datasets/indonesian-lexicon/}, |
|
note = {Accessed 19-03-2024}, |
|
} |
|
""" |
|
|
|
_DATASETNAME = "lex_indo" |
|
|
|
_DESCRIPTION = """This open-source lexicon consists of 2,000 common Indonesian words, with phoneme series attached. |
|
It is intended to be used as the lexicon for an automatic speech recognition system or a text-to-speech system. |
|
The dictionary presents words as well as their pronunciation transcribed with an ARPABET(phone set of CMU)-like phone set. Syllables are separated with dots. |
|
""" |
|
|
|
_HOMEPAGE = "https://magichub.com/datasets/indonesian-lexicon/" |
|
_LICENSE = Licenses.CC_BY_NC_ND_4_0.value |
|
_LOCAL = True |
|
|
|
_URLS = {} |
|
|
|
_SUPPORTED_TASKS = [Tasks.MULTILEXNORM] |
|
|
|
_LANGUAGES = ["ind"] |
|
|
|
_SOURCE_VERSION = "1.0.0" |
|
_SEACROWD_VERSION = "2024.06.20" |
|
|
|
|
|
class LexIndo(datasets.GeneratorBasedBuilder): |
|
"""This open-source lexicon consists of 2,000 common Indonesian words, with phoneme series attached""" |
|
|
|
SOURCE_VERSION = datasets.Version(_SOURCE_VERSION) |
|
SEACROWD_VERSION = datasets.Version(_SEACROWD_VERSION) |
|
SEACROWD_SCHEMA_NAME = "t2t" |
|
|
|
BUILDER_CONFIGS = [ |
|
SEACrowdConfig( |
|
name=f"{_DATASETNAME}_source", |
|
version=SOURCE_VERSION, |
|
description=f"{_DATASETNAME} lexicon with source schema", |
|
schema="source", |
|
subset_id=_DATASETNAME, |
|
) |
|
] + [ |
|
SEACrowdConfig( |
|
name=f"{_DATASETNAME}_seacrowd_{SEACROWD_SCHEMA_NAME}", |
|
version=SEACROWD_VERSION, |
|
description=f"{_DATASETNAME} lexicon with SEACrowd schema", |
|
schema=f"seacrowd_{SEACROWD_SCHEMA_NAME}", |
|
subset_id=_DATASETNAME, |
|
) |
|
] |
|
|
|
DEFAULT_CONFIG_NAME = f"{_DATASETNAME}_source" |
|
|
|
def _info(self) -> datasets.DatasetInfo: |
|
schema = self.config.schema |
|
if schema == "source": |
|
features = datasets.Features({"id": datasets.Value("string"), "word": datasets.Value("string"), "phoneme": datasets.Value("string")}) |
|
else: |
|
features = schemas.text2text_features |
|
|
|
return datasets.DatasetInfo( |
|
description=_DESCRIPTION, |
|
features=features, |
|
homepage=_HOMEPAGE, |
|
license=_LICENSE, |
|
citation=_CITATION, |
|
) |
|
|
|
def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]: |
|
"""Returns SplitGenerators.""" |
|
if self.config.data_dir is None: |
|
raise ValueError("This is a local dataset. Please pass the data_dir kwarg to load_dataset.") |
|
else: |
|
data_dir = self.config.data_dir |
|
|
|
return [ |
|
datasets.SplitGenerator( |
|
name=datasets.Split.TRAIN, |
|
gen_kwargs={ |
|
"filepath": data_dir, |
|
}, |
|
) |
|
] |
|
|
|
def _generate_examples(self, filepath: Path): |
|
"""Yields examples as (key, example) tuples.""" |
|
|
|
try: |
|
with open(f"{filepath}/Indonesian_dic.txt", "r") as f: |
|
data = f.readlines() |
|
except FileNotFoundError: |
|
print("File not found. Please check the file path. Make sure Indonesian_dic.txt is in dest directory") |
|
except IOError: |
|
print("An error occurred while trying to read the file.") |
|
|
|
for idx, text in enumerate(data): |
|
word_i = text.split()[0] |
|
phoneme_i = " ".join(text.split()[1:]) |
|
if self.config.schema == "source": |
|
example = {"id": str(idx), "word": word_i, "phoneme": phoneme_i} |
|
elif self.config.schema == f"seacrowd_{self.SEACROWD_SCHEMA_NAME}": |
|
example = { |
|
"id": str(idx), |
|
"text_1": word_i, |
|
"text_2": phoneme_i, |
|
"text_1_name": _LANGUAGES[-1], |
|
"text_2_name": "phoneme", |
|
} |
|
else: |
|
raise ValueError(f"Invalid config: {self.config.name}") |
|
yield idx, example |
|
|