First version of Hinglish dataset

hinglish.py

@@ -0,0 +1,78 @@
+import csv
+import json
+import os
+import datasets
+
+_ANNOT_URL = [
+    "https://huggingface.co/datasets/ujs/hinglish/data/metadata.csv"
+]
+
+_DATA_URL = [
+    "https://huggingface.co/datasets/ujs/hinglish/data/train.tar.gz",
+    "https://huggingface.co/datasets/ujs/hinglish/data/test.tar.gz"
+]
+
+_DESCRIPTION = """\
+A Hugginface version of the Hindi-English code-switched dataset from OpenSLR-104.
+"""
+
+class HinglishDataset(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version("1.0.0")
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features({
+                "path": datasets.Value("string"),
+                "audio": datasets.Audio(sampling_rate=16_000),
+                "sentence": datasets.Value("string"),
+            }),
+            supervised_keys=("audio", "sentence"),
+        )
+
+    def _split_generators(self, dl_manager):
+        prompts_paths = dl_manager.download(_ANNOT_URL)
+        archive = dl_manager.download(_DATA_URL)
+        train_dir = "hinglish/data/train"
+        test_dir = "hinglish/data/test"
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "prompts_path": prompts_paths["train"],
+                    "path_to_clips": train_dir,
+                    "audio_files": dl_manager.iter_archive(archive),
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "prompts_path": prompts_paths["test"],
+                    "path_to_clips": test_dir,
+                    "audio_files": dl_manager.iter_archive(archive),
+                },
+            ),
+        ]
+    
+    def _generate_examples(self, promts_path, path_to_clips, audio_files):
+        examples = {}
+        with open(promts_path, encoding="utf-8") as f:
+            for row in f:
+                data = row.strip().split(",", 1)
+                audio_path = "/".join([path_to_clips, data[0]])
+                examples[audio_path] = {
+                    "path": audio_path,
+                    "sentence": data[1]
+                }
+        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:
+                    audio = {"path": path, "bytes": f.read()}
+                    yield id_, {**examples[path], "audio": audio}
+                    id += 1
+            elif inside_clips_dir:
+                break