Datasets:

renumics
/

speech_commands_enriched

Tasks:

Audio Classification

Modalities:

Sub-tasks:

keyword-spotting

Languages:

Size:

ArXiv:

Tags:

Libraries:

License:

Dataset card Data Studio Files Files and versions

soeren commited on Aug 21, 2023

Commit

13bba81

·

1 Parent(s): 2b65083

reset to download_and_extract

Files changed (1) hide show

speech_commands_enriched.py +3 -3

speech_commands_enriched.py CHANGED Viewed

@@ -203,21 +203,21 @@ class SpeechCommands(datasets.GeneratorBasedBuilder):
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
                 gen_kwargs={
-                    "archive_path": dl_manager.iter_archive(dl_manager.download(archive_paths["train"])),
                     "metadata": pd.read_parquet(metadata_paths["train"]),
                 },
             ),
             datasets.SplitGenerator(
                 name=datasets.Split.VALIDATION,
                 gen_kwargs={
-                    "archive_path": dl_manager.iter_archive(dl_manager.download(archive_paths["validation"])),
                     "metadata": pd.read_parquet(metadata_paths["validation"]),
                 },
             ),
             datasets.SplitGenerator(
                 name=datasets.Split.TEST,
                 gen_kwargs={
-                    "archive_path": dl_manager.iter_archive(dl_manager.download(archive_paths["test"])),
                     "metadata": pd.read_parquet(metadata_paths["test"]),
                 },
             ),

             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
                 gen_kwargs={
+                    "archive_path": dl_manager.download_and_extract(archive_paths["train"]),
                     "metadata": pd.read_parquet(metadata_paths["train"]),
                 },
             ),
             datasets.SplitGenerator(
                 name=datasets.Split.VALIDATION,
                 gen_kwargs={
+                    "archive_path": dl_manager.download_and_extract(archive_paths["validation"]),
                     "metadata": pd.read_parquet(metadata_paths["validation"]),
                 },
             ),
             datasets.SplitGenerator(
                 name=datasets.Split.TEST,
                 gen_kwargs={
+                    "archive_path": dl_manager.download_and_extract(archive_paths["test"]),
                     "metadata": pd.read_parquet(metadata_paths["test"]),
                 },
             ),