fix config, add config for custom set of languages

voxpopuli.py

@@ -48,7 +48,6 @@ _ASR_ACCENTED_LANGUAGES = [
 
 _LANGUAGES = _ASR_LANGUAGES + _ASR_ACCENTED_LANGUAGES
 
-
 _BASE_DATA_DIR = "https://huggingface.co/datasets/polinaeterna/voxpopuli/resolve/main/data/"
 
 _N_SHARDS_FILE = _BASE_DATA_DIR + "n_files.json"
@@ -61,15 +60,24 @@ _METADATA_PATH = _BASE_DATA_DIR + "{lang}/asr_{split}.tsv"
 class VoxpopuliConfig(datasets.BuilderConfig):
     """BuilderConfig for VoxPopuli."""
 
-    def __init__(self, name, **kwargs):
+    def __init__(self, name, languages=None, **kwargs):
         """
         Args:
-          name: `string`, name of dataset config
+          name: `string` or `List[string]`:
+            name of a config: either one of the supported languages, "all" for all languages (including accented English),
+            or "multilang" for a specific set of languages which must be specified in the `languages` parameter.
+          languages: `List[string]`: custom list of languages for downloading (if config is "multilang")
           **kwargs: keyword arguments forwarded to super.
         """
+        if name == "all":
+            self.languages = _LANGUAGES
+        elif name == "multilang" and languages:
+            self.languages = [languages]
+            name = "+".join(languages)
+        else:
+            self.languages = [name]
+
         super().__init__(name=name, **kwargs)
-        self.languages = _LANGUAGES if name == "all" else [name]
-        # self.data_root_dis = {lang: _DATA_DIR.format(lang) for lang in self.languages}
 
 
 class Voxpopuli(datasets.GeneratorBasedBuilder):
@@ -81,19 +89,22 @@ class Voxpopuli(datasets.GeneratorBasedBuilder):
             name=name,
             version=datasets.Version("1.3.0"),
             )
-        for name in _LANGUAGES + ["all"]
+        for name in _LANGUAGES + ["all", "multilang"]
     ]
-    DEFAULT_WRITER_BATCH_SIZE = 256  # SET THIS TO A LOWER VALUE IF IT USES TOO MUCH RAM SPACE
+    DEFAULT_WRITER_BATCH_SIZE = 256
 
     def _info(self):
         features = datasets.Features(
             {
-                "path": datasets.Value("string"),
+                "audio_id": datasets.Value("string"),
                 "language": datasets.ClassLabel(names=_LANGUAGES),
                 "raw_text": datasets.Value("string"),
                 "normalized_text": datasets.Value("string"),
+                "gender": datasets.Value("string"),  # TODO: ClassVar?
+                "speaker_id": datasets.Value("int64"),
+                "is_gold_transcript": datasets.Value("bool"),
+                "accent": datasets.Value("string"),
                 "audio": datasets.Audio(sampling_rate=16_000),
-                # "segment_id": datasets.Value("int16"),  # TODO
             }
         )
         return datasets.DatasetInfo(
@@ -110,13 +121,16 @@ class Voxpopuli(datasets.GeneratorBasedBuilder):
             n_shards = json.load(f)
 
         audio_urls = defaultdict(dict)
-        for lang in self.config.languages:
-            for split in ["train", "test", "dev"]:
-                audio_urls[split][lang] = [_AUDIO_ARCHIVE_PATH.format(lang=lang, split=split, n_shard=i) for i in range(n_shards[lang][split])]
+        for split in ["train", "test", "dev"]:
+            for lang in self.config.languages:
+                audio_urls[split][lang] = [
+                    _AUDIO_ARCHIVE_PATH.format(lang=lang, split=split, n_shard=i) for i in range(n_shards[lang][split])
+                ]
 
         meta_urls = defaultdict(dict)
         for split in ["train", "test", "dev"]:
-            meta_urls[split][lang] = _METADATA_PATH.format(lang=lang, split=split)
+            for lang in self.config.languages:
+                meta_urls[split][lang] = _METADATA_PATH.format(lang=lang, split=split)
 
         # dl_manager.download_config.num_proc = len(urls)
 
@@ -136,34 +150,41 @@ class Voxpopuli(datasets.GeneratorBasedBuilder):
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
                 gen_kwargs={
-                    "audio_archives": {lang: [dl_manager.iter_archive(archive) for archive in lang_archives] for lang, lang_archives
-                                       in audio_paths["train"].items()},
-                    "local_extracted_audio_archives_paths": local_extracted_audio_paths["train"] if local_extracted_audio_paths else None,
+                    "audio_archives": {
+                        lang: [dl_manager.iter_archive(archive) for archive in lang_archives]
+                        for lang, lang_archives in audio_paths["train"].items()
+                    },
+                    "local_extracted_audio_archives_paths": local_extracted_audio_paths["train"],
                     "metadata_paths": meta_paths["train"],
                 }
             ),
             datasets.SplitGenerator(
                 name=datasets.Split.VALIDATION,
                 gen_kwargs={
-                    "audio_archives": {lang: [dl_manager.iter_archive(archive) for archive in lang_archives] for lang, lang_archives
-                                       in audio_paths["dev"].items()},
-                    "local_extracted_audio_archives_paths": local_extracted_audio_paths["dev"] if local_extracted_audio_paths else None,
+                    "audio_archives": {
+                        lang: [dl_manager.iter_archive(archive) for archive in lang_archives]
+                        for lang, lang_archives in audio_paths["dev"].items()
+                    },
+                    "local_extracted_audio_archives_paths": local_extracted_audio_paths["dev"],
                     "metadata_paths": meta_paths["dev"],
                 }
             ),
             datasets.SplitGenerator(
                 name=datasets.Split.TEST,
                 gen_kwargs={
-                    "audio_archives": {lang: [dl_manager.iter_archive(archive) for archive in lang_archives] for lang, lang_archives
-                                       in audio_paths["test"].items()},
-                    "local_extracted_audio_archives_paths": local_extracted_audio_paths["test"] if local_extracted_audio_paths else None,
+                    "audio_archives": {
+                        lang: [dl_manager.iter_archive(archive) for archive in lang_archives]
+                        for lang, lang_archives in audio_paths["test"].items()
+                    },
+                    "local_extracted_audio_archives_paths": local_extracted_audio_paths["test"],
                     "metadata_paths": meta_paths["test"],
                 }
             ),
         ]
 
     def _generate_examples(self, audio_archives, local_extracted_audio_archives_paths, metadata_paths):
-        assert len(metadata_paths) == len(audio_archives)
+        assert len(metadata_paths) == len(audio_archives) == len(local_extracted_audio_archives_paths)
+        features = ["raw_text", "normalized_text", "speaker_id", "gender", "is_gold_transcript", "accent"]
 
         for lang in self.config.languages:
             meta_path = metadata_paths[lang]
@@ -174,10 +195,10 @@ class Voxpopuli(datasets.GeneratorBasedBuilder):
                 for audio_filename, audio_file in audio_archive:
                     audio_id = audio_filename.split(os.sep)[-1].split(".wav")[0]
                     path = os.path.join(local_extracted_audio_archive_path, audio_filename) if local_extracted_audio_archive_path else audio_filename
+
                     yield audio_id, {
-                        "path": path,
+                        "audio_id": audio_id,
                         "language": lang,
-                        "raw_text": metadata[audio_id]["raw_text"],
-                        "normalized_text": metadata[audio_id]["normalized_text"],
+                        **{feature: metadata[audio_id][feature] for feature in features},
                         "audio": {"path": path, "bytes": audio_file.read()}
                     }