Upload su_id_asr.py with huggingface_hub

su_id_asr.py

@@ -4,14 +4,14 @@ from typing import Dict, List
 
 import datasets
 
-from nusacrowd.utils import schemas
-from nusacrowd.utils.configs import NusantaraConfig
-from nusacrowd.utils.constants import (DEFAULT_NUSANTARA_VIEW_NAME,
+from seacrowd.utils import schemas
+from seacrowd.utils.configs import SEACrowdConfig
+from seacrowd.utils.constants import (DEFAULT_SEACROWD_VIEW_NAME,
                                        DEFAULT_SOURCE_VIEW_NAME, Tasks)
 
 _DATASETNAME = "su_id_asr"
 _SOURCE_VIEW_NAME = DEFAULT_SOURCE_VIEW_NAME
-_UNIFIED_VIEW_NAME = DEFAULT_NUSANTARA_VIEW_NAME
+_UNIFIED_VIEW_NAME = DEFAULT_SEACROWD_VIEW_NAME
 
 _LANGUAGES = ["sun"]
 _LOCAL = False
@@ -44,25 +44,25 @@ _URLs = {
 _SUPPORTED_TASKS = [Tasks.SPEECH_RECOGNITION]
 
 _SOURCE_VERSION = "1.0.0"
-_NUSANTARA_VERSION = "1.0.0"
+_SEACROWD_VERSION = "2024.06.20"
 
 
 class SuIdASR(datasets.GeneratorBasedBuilder):
     """su_id contains ~220K utterances for Sundanese ASR training data."""
 
     BUILDER_CONFIGS = [
-        NusantaraConfig(
+        SEACrowdConfig(
             name="su_id_asr_source",
             version=datasets.Version(_SOURCE_VERSION),
             description="SU_ID_ASR source schema",
             schema="source",
             subset_id="su_id_asr",
         ),
-        NusantaraConfig(
-            name="su_id_asr_nusantara_sptext",
-            version=datasets.Version(_NUSANTARA_VERSION),
+        SEACrowdConfig(
+            name="su_id_asr_seacrowd_sptext",
+            version=datasets.Version(_SEACROWD_VERSION),
             description="SU_ID_ASR Nusantara schema",
-            schema="nusantara_sptext",
+            schema="seacrowd_sptext",
             subset_id="su_id_asr",
         ),
     ]
@@ -80,7 +80,7 @@ class SuIdASR(datasets.GeneratorBasedBuilder):
                     "text": datasets.Value("string"),
                 }
             )
-        elif self.config.schema == "nusantara_sptext":
+        elif self.config.schema == "seacrowd_sptext":
             features = schemas.speech_text_features
 
         return datasets.DatasetInfo(
@@ -107,7 +107,7 @@ class SuIdASR(datasets.GeneratorBasedBuilder):
 
     def _generate_examples(self, filepath: Dict):
 
-        if self.config.schema == "source" or self.config.schema == "nusantara_sptext":
+        if self.config.schema == "source" or self.config.schema == "seacrowd_sptext":
 
             for key, each_filepath in filepath.items():
 
@@ -131,7 +131,7 @@ class SuIdASR(datasets.GeneratorBasedBuilder):
                                     "text": transcription_text,
                                 }
                                 yield audio_id, ex
-                            elif self.config.schema == "nusantara_sptext":
+                            elif self.config.schema == "seacrowd_sptext":
                                 ex = {
                                     "id": audio_id,
                                     "speaker_id": speaker_id,