holylovenia commited on
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f8da5cc
1 Parent(s): f42228d

Upload titml_idn.py with huggingface_hub

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  1. titml_idn.py +14 -14
titml_idn.py CHANGED
@@ -5,13 +5,13 @@ import datasets
5
  import json
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  import os
7
 
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- from nusacrowd.utils import schemas
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- from nusacrowd.utils.configs import NusantaraConfig
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- from nusacrowd.utils.constants import Tasks, DEFAULT_SOURCE_VIEW_NAME, DEFAULT_NUSANTARA_VIEW_NAME
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  _DATASETNAME = "titml_idn"
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  _SOURCE_VIEW_NAME = DEFAULT_SOURCE_VIEW_NAME
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- _UNIFIED_VIEW_NAME = DEFAULT_NUSANTARA_VIEW_NAME
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  _LANGUAGES = ["ind"] # We follow ISO639-3 language code (https://iso639-3.sil.org/code_tables/639/data)
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  _LOCAL = False
@@ -31,32 +31,32 @@ TITML-IDN (Tokyo Institute of Technology Multilingual - Indonesian) is collected
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  _HOMEPAGE = "http://research.nii.ac.jp/src/en/TITML-IDN.html"
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- _LICENSE = "For research purposes only. If you use this corpus, you have to cite (Lestari et al, 2006)."
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  _URLs = {"titml-idn": "https://huggingface.co/datasets/holylovenia/TITML-IDN/resolve/main/IndoLVCSR.zip"}
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  _SUPPORTED_TASKS = [Tasks.SPEECH_RECOGNITION]
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  _SOURCE_VERSION = "1.0.0"
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- _NUSANTARA_VERSION = "1.0.0"
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  class TitmlIdn(datasets.GeneratorBasedBuilder):
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  """TITML-IDN is a speech recognition dataset containing Indonesian speech collected with transcriptions from newpaper and magazine articles."""
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  BUILDER_CONFIGS = [
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- NusantaraConfig(
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  name="titml_idn_source",
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  version=datasets.Version(_SOURCE_VERSION),
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  description="TITML-IDN source schema",
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  schema="source",
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  subset_id="titml_idn",
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  ),
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- NusantaraConfig(
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- name="titml_idn_nusantara_sptext",
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- version=datasets.Version(_NUSANTARA_VERSION),
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  description="TITML-IDN Nusantara schema",
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- schema="nusantara_sptext",
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  subset_id="titml_idn",
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  ),
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  ]
@@ -74,7 +74,7 @@ class TitmlIdn(datasets.GeneratorBasedBuilder):
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  "text": datasets.Value("string"),
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  }
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  )
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- elif self.config.schema == "nusantara_sptext":
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  features = schemas.speech_text_features
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  return datasets.DatasetInfo(
@@ -98,7 +98,7 @@ class TitmlIdn(datasets.GeneratorBasedBuilder):
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  def _generate_examples(self, filepath: Path, n_speakers=20):
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- if self.config.schema == "source" or self.config.schema == "nusantara_sptext":
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  for speaker_id in range(1, n_speakers + 1):
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  speaker_id = str(speaker_id).zfill(2)
@@ -121,7 +121,7 @@ class TitmlIdn(datasets.GeneratorBasedBuilder):
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  "text": text,
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  }
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  yield audio_id, ex
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- elif self.config.schema == "nusantara_sptext":
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  ex = {
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  "id": audio_id,
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  "speaker_id": speaker_id,
 
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  import json
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  import os
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+ from seacrowd.utils import schemas
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+ from seacrowd.utils.configs import SEACrowdConfig
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+ from seacrowd.utils.constants import Licenses, Tasks, DEFAULT_SOURCE_VIEW_NAME, DEFAULT_SEACROWD_VIEW_NAME
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  _DATASETNAME = "titml_idn"
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  _SOURCE_VIEW_NAME = DEFAULT_SOURCE_VIEW_NAME
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+ _UNIFIED_VIEW_NAME = DEFAULT_SEACROWD_VIEW_NAME
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  _LANGUAGES = ["ind"] # We follow ISO639-3 language code (https://iso639-3.sil.org/code_tables/639/data)
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  _LOCAL = False
 
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  _HOMEPAGE = "http://research.nii.ac.jp/src/en/TITML-IDN.html"
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+ _LICENSE = Licenses.OTHERS.value + " | For research purposes only. If you use this corpus, you have to cite (Lestari et al, 2006)."
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  _URLs = {"titml-idn": "https://huggingface.co/datasets/holylovenia/TITML-IDN/resolve/main/IndoLVCSR.zip"}
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  _SUPPORTED_TASKS = [Tasks.SPEECH_RECOGNITION]
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  _SOURCE_VERSION = "1.0.0"
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+ _SEACROWD_VERSION = "2024.06.20"
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43
 
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  class TitmlIdn(datasets.GeneratorBasedBuilder):
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  """TITML-IDN is a speech recognition dataset containing Indonesian speech collected with transcriptions from newpaper and magazine articles."""
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  BUILDER_CONFIGS = [
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+ SEACrowdConfig(
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  name="titml_idn_source",
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  version=datasets.Version(_SOURCE_VERSION),
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  description="TITML-IDN source schema",
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  schema="source",
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  subset_id="titml_idn",
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  ),
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+ SEACrowdConfig(
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+ name="titml_idn_seacrowd_sptext",
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+ version=datasets.Version(_SEACROWD_VERSION),
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  description="TITML-IDN Nusantara schema",
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+ schema="seacrowd_sptext",
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  subset_id="titml_idn",
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  ),
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  ]
 
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  "text": datasets.Value("string"),
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  }
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  )
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+ elif self.config.schema == "seacrowd_sptext":
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  features = schemas.speech_text_features
79
 
80
  return datasets.DatasetInfo(
 
98
 
99
  def _generate_examples(self, filepath: Path, n_speakers=20):
100
 
101
+ if self.config.schema == "source" or self.config.schema == "seacrowd_sptext":
102
 
103
  for speaker_id in range(1, n_speakers + 1):
104
  speaker_id = str(speaker_id).zfill(2)
 
121
  "text": text,
122
  }
123
  yield audio_id, ex
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+ elif self.config.schema == "seacrowd_sptext":
125
  ex = {
126
  "id": audio_id,
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  "speaker_id": speaker_id,