addding previous code

bn_emotion_speech_corpus.py

@@ -1,90 +1,55 @@
-import json
-import os
-
 import datasets
 
 _CITATION = """\
+
 """
 
 _DESCRIPTION = """\
-The corpus contains roughly 360 hours of audio and transcripts in Kannada language. The transcripts have beed de-duplicated using exact match deduplication.
-"""
 
+"""
 _HOMEPAGE = ""
 
-_LICENSE = "https://creativecommons.org/licenses/"
-
+_LICENSE = ""
 
-_METADATA_URLS = {
-    "train": "train.jsonl",
-}
-_URLS = {
-    "train": "subesco.tar.gz",
-    
-}
+#_REPO = "https://huggingface.co/datasets/sustcsenlp/SUBESCO/resolve/main/corpus/speech/subesco.tar.gz"
 
-class KannadaASRCorpus(datasets.GeneratorBasedBuilder):
-    """Kannada ASR Corpus contains transcribed speech corpus for training ASR systems for Kannada language."""
+class ImageSet(datasets.GeneratorBasedBuilder):
+    """"""
 
-    VERSION = datasets.Version("1.1.0")
     def _info(self):
-        features = datasets.Features(
-            {
-                "path": datasets.Value("string"),
-                "audio": datasets.Audio(sampling_rate=16000),
-                "speaker_gender": datasets.Value("string"),
-                "speaker_number": datasets.Value("int32"),
-                "speaker_name": datasets.Value("string"),
-                "sentence_number": datasets.Value("int32"),
-                "emotional_state": datasets.Value("string"),
-                "take_number": datasets.Value("int32"),
-            }
-        )
         return datasets.DatasetInfo(
             description=_DESCRIPTION,
-            features=features,
+            features=datasets.Features(
+                {
+                    'text': datasets.Value("string"),
+                    "audio": datasets.Audio(sampling_rate=16000),
+                }
+            ),
             supervised_keys=None,
             homepage=_HOMEPAGE,
-            license=_LICENSE,
             citation=_CITATION,
         )
 
     def _split_generators(self, dl_manager):
-        metadata_paths = dl_manager.download(_METADATA_URLS)
-        train_archive = dl_manager.download(_URLS["train"])
-        local_extracted_train_archive = dl_manager.extract(train_archive) if not dl_manager.is_streaming else None
-        train_dir = "train"
-
+        audio_archive = dl_manager.download("https://huggingface.co/datasets/sustcsenlp/SUBESCO/resolve/main/corpus/speech/subesco.tar.gz")
+        audio_iters = dl_manager.iter_archive(audio_archive)
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
                 gen_kwargs={
-                    "metadata_path": metadata_paths["train"],
-                    "local_extracted_archive": local_extracted_train_archive,
-                    "path_to_clips": train_dir,
-                    "audio_files": dl_manager.iter_archive(train_archive),
-                },
-            ),   
+                    "audios": audio_iters
+                }
+            ),
         ]
-        
-    def _generate_examples(self, metadata_path, local_extracted_archive, path_to_clips, audio_files):
-        """Yields examples as (key, example) tuples."""
-        examples = {}
-        with open(metadata_path, encoding="utf-8") as f:
-            for key, row in enumerate(f):
-                data = json.loads(row)
-                examples[data["path"]] = data
-        inside_clips_dir = False
-        id_ = 0
-        for path, f in audio_files:
-            if path.startswith(path_to_clips):
-                inside_clips_dir = True
-                if path in examples:
-                    result = examples[path]
-                    path = os.path.join(local_extracted_archive, path) if local_extracted_archive else path
-                    result["audio"] = {"path": path, "bytes": f.read()}
-                    result["path"] = path
-                    yield id_, result
-                    id_ += 1
-            elif inside_clips_dir:
-                break
+
+    def _generate_examples(self, audios):
+        """This function returns the examples in the raw (text) form."""
+        idx = 0
+        for filepath, audio in audios:
+            description = filepath.split('/')[-1][:-4]
+            #description = description.replace('_', ' ')
+            yield idx, {
+                "audio": {"path": filepath, "bytes": audio.read()},
+                "text": description,
+            }
+            idx += 1