Delete NURC-SP_ENTOA_TTS.py

NURC-SP_ENTOA_TTS.py

@@ -1,303 +0,0 @@
-import csv
-import datasets
-from datasets import BuilderConfig, GeneratorBasedBuilder, DatasetInfo, SplitGenerator, Split
-from pathlib import Path
-
-_PROMPTS_PROSODIC_URLS = {
-    "dev": "prosodic/validation.csv",
-    "train": "prosodic/train.csv",
-}
-
-_PROMPTS_AUDIO_CORPUS_URLS = {
-    "dev": "audioCorpus/validation.csv",
-    "train": "audioCorpus/train.csv",
-}
-
-_PROMPTS_AUTOMATIC_URLS = {
-    "dev": "automatic/validation.csv",
-    "train": "automatic/train.csv",
-}
-
-_PROMPTS_TEST_URLS = {
-    "test": "test/test.csv",
-}
-
-_ARCHIVES_PROSODIC = {
-    "dev": "prosodic/audios.tar.gz",
-    "train": "prosodic/audios.tar.gz",
-}
-
-_ARCHIVES_AUDIO_CORPUS = {
-    "dev": "audioCorpus/audios.tar.gz",
-    "train": "audioCorpus/audios.tar.gz",
-}
-
-_ARCHIVES_AUTOMATIC = {
-    "train": "automatic/nurc_cm_automatic_segmented_audios.zip",
-    "dev": "automatic/nurc_cm_automatic_segmented_audios.zip",
-}
-
-_ARCHIVES_TEST = {
-    "test": "test/test.zip",
-}
-
-_PATH_TO_CLIPS = {
-    "dev": "",
-    "train": "",
-    "test": "",
-}
-
-
-class NurcSPConfig(BuilderConfig):
-    def __init__(self, prompts_type, **kwargs):
-        super().__init__(**kwargs)
-        self.prompts_type = prompts_type
-
-
-class NurcSPDataset(GeneratorBasedBuilder):
-    BUILDER_CONFIGS = [
-        NurcSPConfig(name="audioCorpus", description="Audio Corpus audio prompts", prompts_type="audioCorpus"),
-        NurcSPConfig(name="prosodic", description="Prosodic audio prompts", prompts_type="prosodic"),
-        NurcSPConfig(name="automatic", description="Automatic audio prompts", prompts_type="automatic"),
-        NurcSPConfig(name="test", description="Test audio prompts", prompts_type="test"),
-    ]
-
-    def _info(self):
-        if self.config.name == "prosodic":
-            return DatasetInfo(
-                features=datasets.Features(
-                    {
-                        "path": datasets.Value("string"),
-                        "name": datasets.Value("string"),
-                        "speaker": datasets.Value("string"),
-                        "start_time": datasets.Value("string"),
-                        "end_time": datasets.Value("string"),
-                        "normalized_text": datasets.Value("string"),
-                        "text": datasets.Value("string"),
-                        "duration": datasets.Value("string"),
-                        "type": datasets.Value("string"),
-                        "year": datasets.Value("string"),
-                        "gender": datasets.Value("string"),
-                        "age_range": datasets.Value("string"),
-                        "total_duration": datasets.Value("string"),
-                        "quality": datasets.Value("string"),
-                        "theme": datasets.Value("string"),
-                        "audio": datasets.Audio(sampling_rate=16_000, mono=True),
-                    }
-                )
-            )
-        elif self.config.name == "audioCorpus":
-            return 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, mono=True),
-                    }
-                )
-            )
-        elif self.config.name == "automatic":
-            return DatasetInfo(
-                features=datasets.Features(
-                    {
-                        "path": datasets.Value("string"),
-                        "name": datasets.Value("string"),
-                        "speaker": datasets.Value("string"),
-                        "start_time": datasets.Value("string"),
-                        "end_time": datasets.Value("string"),
-                        "text": datasets.Value("string"),
-                        "duration": datasets.Value("string"),
-                        "audio": datasets.Audio(sampling_rate=16_000, mono=True),
-                    }
-                )
-            )
-        elif self.config.name == "test":
-            return DatasetInfo(
-                features=datasets.Features(
-                    {
-                        "path": datasets.Value("string"),
-                        "name": datasets.Value("string"),
-                        "speaker": datasets.Value("string"),  
-                        "start_time": datasets.Value("string"),
-                        "end_time": datasets.Value("string"),
-                        "text": datasets.Value("string"),
-                        "duration": datasets.Value("string"),
-                        "audio": datasets.Audio(sampling_rate=16_000, mono=True),                  
-                    }
-                )
-            )
-
-
-    def _split_generators(self, dl_manager):
-        if self.config.prompts_type == "prosodic":
-            prompts_urls = _PROMPTS_PROSODIC_URLS
-            archive_link = _ARCHIVES_PROSODIC
-        elif self.config.prompts_type == "audioCorpus":
-            prompts_urls = _PROMPTS_AUDIO_CORPUS_URLS
-            archive_link = _ARCHIVES_AUDIO_CORPUS
-        elif self.config.prompts_type == "automatic":
-            prompts_urls = _PROMPTS_AUTOMATIC_URLS
-            archive_link = _ARCHIVES_AUTOMATIC
-        elif self.config.prompts_type == "test":
-            prompts_urls = _PROMPTS_TEST_URLS
-            archive_link = _ARCHIVES_TEST
-        else:
-            return
-
-        prompts_path = dl_manager.download(prompts_urls)
-        archive = dl_manager.download(archive_link)
-
-        if self.config.prompts_type == "prosodic" or self.config.prompts_type == "audioCorpus":
-            return [
-                SplitGenerator(
-                    name=Split.VALIDATION,
-                    gen_kwargs={
-                        "prompts_path": prompts_path["dev"],
-                        "path_to_clips": _PATH_TO_CLIPS["dev"],
-                        "audio_files": dl_manager.iter_archive(archive["dev"]),
-                        "split_name": "validation"
-                    }
-                ),
-                SplitGenerator(
-                    name=Split.TRAIN,
-                    gen_kwargs={
-                        "prompts_path": prompts_path["train"],
-                        "path_to_clips": _PATH_TO_CLIPS["train"],
-                        "audio_files": dl_manager.iter_archive(archive["train"]),
-                        "split_name": "train"
-                    }
-                ),
-            ]
-        elif self.config.prompts_type == "automatic":
-            return [
-                SplitGenerator(
-                    name=Split.VALIDATION,
-                    gen_kwargs={
-                        "prompts_path": prompts_path["dev"],
-                        "path_to_clips": _PATH_TO_CLIPS["dev"],
-                        "audio_files": dl_manager.iter_archive(archive["dev"]),
-                        "split_name": "validation"
-                    }
-                ),
-                SplitGenerator(
-                    name=Split.TRAIN,
-                    gen_kwargs={
-                        "prompts_path": prompts_path["train"],
-                        "path_to_clips": _PATH_TO_CLIPS["train"],
-                        "audio_files": dl_manager.iter_archive(archive["train"]),
-                        "split_name": "train"
-                    }
-                ),
-            ]
-        elif self.config.prompts_type == "test":
-            return[
-                SplitGenerator(
-                    name=Split.TEST,
-                    gen_kwargs={
-                        "prompts_path": prompts_path["test"],
-                        "path_to_clips": _PATH_TO_CLIPS["test"],
-                        "audio_files": dl_manager.iter_archive(archive["test"]),
-                        "split_name": "test"
-                    }
-                ),
-            ]
-
-    def _generate_examples(self, prompts_path, path_to_clips, audio_files, split_name):
-        examples = {}
-        csv_paths = []
-
-        with open(prompts_path, "r", encoding="utf-8") as f:
-            if self.config.prompts_type == "test":
-                csv_reader = csv.DictReader(f, delimiter=";")  # Explicitly set delimiter
-            else:
-                csv_reader = csv.DictReader(f)
-                
-            if self.config.prompts_type == "prosodic":
-                for row in csv_reader:
-                    file_path = Path(row['path']).as_posix()
-                    examples[file_path] = {
-                        "path": row['path'],
-                        "name": row['name'],
-                        "speaker": row['speaker'],
-                        "start_time": row['start_time'],
-                        "end_time": row['end_time'],
-                        "normalized_text": row['normalized_text'],
-                        "text": row['text'],
-                        "duration": row['duration'],
-                        "type": row['type'],
-                        "year": row['year'],
-                        "gender": row['gender'],
-                        "age_range": row['age_range'],
-                        "total_duration": row['total_duration'],
-                        "quality": row['quality'],
-                        "theme": row['theme'],
-                    }
-                    csv_paths.append(file_path)
-            elif self.config.prompts_type == "audioCorpus":
-                for row in csv_reader:
-                    file_path = Path(row['file_path']).as_posix()
-                    examples[file_path] = {
-                        "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'],
-                    }
-                    csv_paths.append(file_path)
-            elif self.config.prompts_type == "automatic":
-                for row in csv_reader:
-                    file_path = Path(row['path']).as_posix()
-                    examples[file_path] = {
-                        "path": row['path'],
-                        "name": row['name'],
-                        "speaker": row['speaker'],
-                        "start_time": row['start_time'],
-                        "end_time": row['end_time'],
-                        "text": row['text'],
-                        "duration": row['duration'],
-                    }
-                    csv_paths.append(file_path)
-            elif self.config.prompts_type == "test":
-                for row in csv_reader:
-                    file_path = Path(row['path']).as_posix()
-                    examples[file_path] = {
-                        "path": row['path'],
-                        "name": row['name'],
-                        "speaker": row['speaker'],
-                        "start_time": row['start_time'],
-                        "end_time": row['end_time'],
-                        "text": row['text'],
-                        "duration": row['duration'],
-                    }
-                    csv_paths.append(file_path)
-
-        id_ = 0
-        for path, f in audio_files:
-            path = Path(path).as_posix()
-            if path.startswith(path_to_clips) and path in examples:
-                audio = {"path": path, "bytes": f.read()}
-                yield id_, {**examples[path], "audio": audio}
-                id_ += 1