Update czech_parliament_plenary_hearings.py

czech_parliament_plenary_hearings.py

@@ -1,8 +1,10 @@
-from datasets import Dataset, GeneratorBasedBuilder, Features
 import os
 import tarfile
-import librosa
+
+import soundfile as sf
+
 import datasets
+
 _LICENSE = "https://creativecommons.org/licenses/by/4.0/"
 _HOMEPAGE = "https://lindat.mff.cuni.cz/repository/xmlui/handle/11234/1-3126"
 _DATASET_URL = "https://lindat.mff.cuni.cz/repository/xmlui/bitstream/handle/11234/1-3126/snemovna.tar.xz"
@@ -21,9 +23,8 @@ _CITATION = """\
  year = {2019} } """
 
 
-class CzechParliamentPlenaryHearings(GeneratorBasedBuilder):
-    def __init__(self, **kwargs):
-        super().__init__(**kwargs)
+class MyAudioDataset(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version("1.0.0")
 
     def _info(self):
         return datasets.DatasetInfo(
@@ -31,8 +32,9 @@ class CzechParliamentPlenaryHearings(GeneratorBasedBuilder):
             features=datasets.Features(
                 {
                     "id": datasets.Value("string"),
-                    "audio": datasets.features.Audio(sampling_rate=16000),
-                    "transcription": datasets.Value("string")
+                    "audio": datasets.features.Audio(),
+                    "transcription": datasets.Value("string"),
+                    "audio_sampling_rate": datasets.Value("int32"),
                 }
             ),
             supervised_keys=None,
@@ -42,44 +44,40 @@ class CzechParliamentPlenaryHearings(GeneratorBasedBuilder):
         )
 
     def _split_generators(self, dl_manager):
-        archive_path = dl_manager.download(_DATASET_URL)
-        data_dir = os.path.join(archive_path, 'ASR_DATA')
-        splits = ("train", "dev", "test")
+        archive_path = dl_manager.download_and_extract(_DATASET_URL)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"directory": os.path.join(
+                    archive_path, "ASR_DATA", "train")},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={"directory": os.path.join(
+                    archive_path, "ASR_DATA", "dev")},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={"directory": os.path.join(
+                    archive_path, "ASR_DATA", "test")},
+            ),
+        ]
 
-        split_names = {
-            "train": datasets.Split.TRAIN,
-            "dev": datasets.Split.VALIDATION,
-            "test": datasets.Split.TEST,
-        }
-        split_generators = []
-        for split in splits:
-            split_dir = os.path.join(data_dir, split)
-            split_generators.append(
-                datasets.SplitGenerator(
-                    name=split_names.get(split, split),
-                    gen_kwargs={'archive_path': archive_path, 'split_dir': split_dir})
-            )
-        return split_generators
+    def _generate_examples(self, directory):
+        for root, _, files in os.walk(directory):
+            for filename in files:
+                if filename.endswith(".wav"):
+                    audio_path = os.path.join(root, filename)
+                    transcription_path = os.path.join(root, filename + ".trn")
 
-    def _generate_examples(self, split_dir, archive_path):
-        for folder_name in os.listdir(split_dir):
-            folder_path = os.path.join(split_dir, folder_name)
-            if os.path.isdir(folder_path):
-                for file_name in os.listdir(folder_path):
-                    file_path = os.path.join(folder_path, file_name)
-                    if file_name.endswith('.trn'):
-                        with open(file_path, 'r') as f:
-                            transcription = f.read().strip()
-                    elif file_name.endswith('.wav'):
-                        with self._dl_manager.iter_archive(archive_path, filter_func=lambda x: x.path == file_path) as files:
-                            audio_file = next(files)
-                            audio_path = os.path.join(
-                                folder_name, audio_file.path.split('/')[-1])
-                            audio, sr = librosa.load(audio_file, sr=16000)
+                    # Load audio and transcription
+                    audio, sampling_rate = sf.read(audio_path)
+                    with open(transcription_path, "r", encoding="utf-8") as f:
+                        transcription = f.read().strip()
 
-                yield f'{folder_name}/{audio_file.path.split("/")[-1]}', {
-                    'audio': {
-                        'path': audio_path, 'bytes': audio
-                    },
-                    'transcription': transcription,
-                }
+                    yield f"{audio_path}-{transcription}", {
+                        "audio": audio,
+                        "transcription": transcription,
+                        "audio_sampling_rate": sampling_rate,
+                    }