updated

release_stats.py

@@ -1,7 +1,12 @@
 STATS = {
     "name": "Librivox-Indonesia",
     "bundleURLTemplate": "https://huggingface.co/datasets/cahya/test01/resolve/main/audio.tgz",
-    "version": "1.0",
+    "version": "1.0.0",
     "date": "",
-    "locales": {'reportedSentences': 261, 'buckets': {'dev': 3218, 'invalidated': 2454, 'other': 22787, 'reported': 260, 'test': 3622, 'train': 5043, 'validated': 23132}, 'duration': 196639788, 'clips': 48373, 'splits': {'accent': {'': 1}, 'age': {'': 0.26, 'twenties': 0.39, 'thirties': 0.07, 'teens': 0.26, 'fifties': 0, 'fourties': 0.02}, 'gender': {'': 0.26, 'male': 0.41, 'female': 0.29, 'other': 0.04}}, 'users': 416, 'size': 1253048208, 'checksum': '874e959e2ca1aacc502ff969a3e54de792dd41e4f672ae1fd9d38213f4bf4139', 'avgDurationSecs': 4.065, 'validDurationSecs': 94033.274, 'totalHrs': 54.62, 'validHrs': 26.12}
-}
+    "locales": {
+        "id": {'reportedSentences': 261, 'buckets': {'dev': 3218, 'invalidated': 2454, 'other': 22787, 'reported': 260, 'test': 3622, 'train': 5043, 'validated': 23132}, 'duration': 196639788, 'clips': 48373, 'splits': {'accent': {'': 1}, 'age': {'': 0.26, 'twenties': 0.39, 'thirties': 0.07, 'teens': 0.26, 'fifties': 0, 'fourties': 0.02}, 'gender': {'': 0.26, 'male': 0.41, 'female': 0.29, 'other': 0.04}}, 'users': 416, 'size': 1253048208, 'checksum': '874e959e2ca1aacc502ff969a3e54de792dd41e4f672ae1fd9d38213f4bf4139', 'avgDurationSecs': 4.065, 'validDurationSecs': 94033.274, 'totalHrs': 54.62, 'validHrs': 26.12},
+        "sun": {'reportedSentences': 261, 'buckets': {'dev': 3218, 'invalidated': 2454, 'other': 22787, 'reported': 260, 'test': 3622, 'train': 5043, 'validated': 23132}, 'duration': 196639788, 'clips': 48373, 'splits': {'accent': {'': 1}, 'age': {'': 0.26, 'twenties': 0.39, 'thirties': 0.07, 'teens': 0.26, 'fifties': 0, 'fourties': 0.02}, 'gender': {'': 0.26, 'male': 0.41, 'female': 0.29, 'other': 0.04}}, 'users': 416, 'size': 1253048208, 'checksum': '874e959e2ca1aacc502ff969a3e54de792dd41e4f672ae1fd9d38213f4bf4139', 'avgDurationSecs': 4.065, 'validDurationSecs': 94033.274, 'totalHrs': 54.62, 'validHrs': 26.12}
+    },
+    'totalDuration': 72782088097, 'totalValidDurationSecs': 53904443, 'totalHrs': 20217, 'totalValidHrs': 14973
+}
+

test01.py

@@ -30,7 +30,7 @@ from .release_stats import STATS
 _CITATION = """\
 """
 
-_HOMEPAGE = "https://commonvoice.mozilla.org/en/datasets"
+_HOMEPAGE = "https://huggingface.co/indonesian-nlp/librivox-indonesia"
 
 _LICENSE = "https://creativecommons.org/publicdomain/zero/1.0/"
 
@@ -49,10 +49,8 @@ class Test01Config(datasets.BuilderConfig):
         self.size_bytes = kwargs.pop("size_bytes", None)
         self.size_human = size_str(self.size_bytes)
         description = (
-            f"Common Voice speech to text dataset in {self.language} released on {self.release_date}. "
-            f"The dataset comprises {self.validated_hr} hours of validated transcribed speech data "
-            f"out of {self.total_hr} hours in total from {self.num_speakers} speakers. "
-            f"The dataset contains {self.num_clips} audio clips and has a size of {self.size_human}."
+            f"LibriVox-Indonesia speech to text dataset in {self.language} released on {self.release_date}. "
+            f"The dataset comprises {self.validated_hr} hours of transcribed speech data"
         )
         super(Test01Config, self).__init__(
             name=name,
@@ -91,17 +89,11 @@ class Test01(datasets.GeneratorBasedBuilder):
         )
         features = datasets.Features(
             {
-                "client_id": datasets.Value("string"),
                 "path": datasets.Value("string"),
-                "audio": datasets.features.Audio(sampling_rate=48_000),
+                "language": datasets.Value("string"),
+                "reader": datasets.Value("string"),
                 "sentence": datasets.Value("string"),
-                "up_votes": datasets.Value("int64"),
-                "down_votes": datasets.Value("int64"),
-                "age": datasets.Value("string"),
-                "gender": datasets.Value("string"),
-                "accent": datasets.Value("string"),
-                "locale": datasets.Value("string"),
-                "segment": datasets.Value("string"),
+                "audio": datasets.features.Audio(sampling_rate=48_000)
             }
         )
 
@@ -120,11 +112,13 @@ class Test01(datasets.GeneratorBasedBuilder):
 
     def _split_generators(self, dl_manager):
         """Returns SplitGenerators."""
+        """
         hf_auth_token = dl_manager.download_config.use_auth_token
         if hf_auth_token is None:
             raise ConnectionError(
                 "Please set use_auth_token=True or use_auth_token='<TOKEN>' to download this dataset"
             )
+        """
 
         bundle_url_template = STATS["bundleURLTemplate"]
         bundle_version = bundle_url_template.split("/")[0]
@@ -145,7 +139,7 @@ class Test01(datasets.GeneratorBasedBuilder):
                 gen_kwargs={
                     "local_extracted_archive": local_extracted_archive,
                     "archive_iterator": dl_manager.iter_archive(archive_path),
-                    "metadata_filepath": "/".join([path_to_data, "train.tsv"]) if path_to_data else "train.tsv",
+                    "metadata_filepath": "/".join([path_to_data, "audio_transcription.csv"]) if path_to_data else "audio_transcription.csv",
                     "path_to_clips": path_to_clips,
                 },
             ),
@@ -161,36 +155,24 @@ class Test01(datasets.GeneratorBasedBuilder):
         """Yields examples."""
         data_fields = list(self._info().features.keys())
         metadata = {}
-        metadata_found = False
+        filepath = local_extracted_archive + "/audio/audio_transcription.csv"
+        with open(filepath, "r") as f:
+            lines = (line for line in f)
+            utterances = csv.DictReader(lines)
+            for row in utterances:
+                row["path"] = os.path.join(path_to_clips, row["path"])
+                # if data is incomplete, fill with empty values
+                for field in data_fields:
+                    if field not in row:
+                        row[field] = ""
+                metadata[row["path"]] = row
         for path, f in archive_iterator:
-            if path == metadata_filepath:
-                metadata_found = True
-                lines = (line.decode("utf-8") for line in f)
-                reader = csv.DictReader(lines, delimiter="\t", quoting=csv.QUOTE_NONE)
-                for row in reader:
-                    # set absolute path for mp3 audio file
-                    if not row["path"].endswith(".mp3"):
-                        row["path"] += ".mp3"
-                    row["path"] = os.path.join(path_to_clips, row["path"])
-                    # accent -> accents in CV 8.0
-                    if "accents" in row:
-                        row["accent"] = row["accents"]
-                        del row["accents"]
-                    # if data is incomplete, fill with empty values
-                    for field in data_fields:
-                        if field not in row:
-                            row[field] = ""
-                    metadata[row["path"]] = row
-            elif path.startswith(path_to_clips):
-                assert metadata_found, "Found audio clips before the metadata TSV file."
-                if not metadata:
-                    break
-                if path in metadata:
-                    result = dict(metadata[path])
-                    # set the audio feature and the path to the extracted file
-                    path = os.path.join(local_extracted_archive, path) if local_extracted_archive else path
-                    result["audio"] = {"path": path, "bytes": f.read()}
-                    # set path to None if the audio file doesn't exist locally (i.e. in streaming mode)
-                    result["path"] = path if local_extracted_archive else None
-
-                    yield path, result
+            if path.endswith(".mp3") and path in metadata:
+                result = dict(metadata[path])
+                # set the audio feature and the path to the extracted file
+                path = os.path.join(local_extracted_archive, path) if local_extracted_archive else path
+                result["audio"] = {"path": path, "bytes": f.read()}
+                # set path to None if the audio file doesn't exist locally (i.e. in streaming mode)
+                result["path"] = path if local_extracted_archive else None
+
+                yield path, result

usage.py

@@ -2,7 +2,7 @@ from datasets import load_dataset
 
 
 def main():
-    ds = load_dataset("./test01.py", "sun")
+    ds = load_dataset("./test01.py", "sun", ignore_verifications=True)
     print(ds)