Create nurc-sp-dev.py

nurc-sp-dev.py

@@ -0,0 +1,103 @@
+import csv
+import datasets
+
+_PROMPTS_URLS = {
+    "dev": "data/audios_dev_metadata.csv",
+}
+
+_ARCHIVES = {
+    "dev": "data/dev.tar",
+}
+
+_PATH_TO_CLIPS = {
+    "dev": "dev",
+}
+
+class NurcSPDataset(datasets.GeneratorBasedBuilder):
+    def _info(self):
+        return datasets.DatasetInfo(
+            features=datasets.Features(
+                {
+                    "audio_name": datasets.Value("string"),
+                    "file_path": datasets.Value("string"),
+                    "text": datasets.Value("string"),
+                    "start_time": datasets.Value("string"),
+                    "end_time": datasets.Value("string"),
+                    "duration": datasets.Value("string"),
+                    "quality": datasets.Value("string"),
+                    "speech_genre": datasets.Value("string"),
+                    "speech_style": datasets.Value("string"),
+                    "variety": datasets.Value("string"),
+                    "accent": datasets.Value("string"),
+                    "sex": datasets.Value("string"),
+                    "age_range": datasets.Value("string"),
+                    "num_speakers": datasets.Value("string"),
+                    "speaker_id": datasets.Value("string"),
+                    "audio": datasets.Audio(sampling_rate=16_000),
+                }
+            )
+        )
+
+    def _split_generators(self, dl_manager):
+        prompts_path = dl_manager.download(_PROMPTS_URLS)
+        archive = dl_manager.download(_ARCHIVES)
+
+        return [
+            datasets.SplitGenerator(
+                name = datasets.Split.VALIDATION,
+                gen_kwargs = {
+                    "prompts_path": prompts_path["dev"],
+                    "path_to_clips": _PATH_TO_CLIPS["dev"],
+                    "audio_files": dl_manager.iter_archive(archive["dev"]),
+                }
+            ),
+        ]
+
+    def _generate_examples(self, prompts_path, path_to_clips, audio_files):
+        examples = {}
+        with open(prompts_path, "r") as f:
+            csv_reader = csv.DictReader(f)
+            for row in csv_reader:
+                audio_name = row['audio_name']
+                file_path = row['file_path']
+                text = row['text']
+                start_time = row['start_time']
+                end_time = row['end_time']
+                duration = row['duration']
+                quality = row['quality']
+                speech_genre = row['speech_genre']
+                speech_style = row['speech_style']
+                variety = row['variety']
+                accent = row['accent']
+                sex = row['sex']
+                age_range = row['age_range']
+                num_speakers = row['num_speakers']
+                speaker_id = row['speaker_id']
+                examples[file_path] = {
+                    "audio_name": audio_name,
+                    "file_path": file_path,
+                    "text": text,
+                    "start_time": start_time,
+                    "end_time": end_time,
+                    "duration": duration,
+                    "quality": quality,
+                    "speech_genre": speech_genre,
+                    "speech_style": speech_style,
+                    "variety": variety,
+                    "accent": accent,
+                    "sex": sex,
+                    "age_range": age_range,
+                    "num_speakers": num_speakers,
+                    "speaker_id": speaker_id,
+                }
+        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