Host data files (#3)

- Host data files (3bd30b56c1c07063fd118d5e084b460d0db5a634)
- Update loading script (ebdefc1c4d373aff38fa5d42d21d6208c0379602)
- Delete legacy metadata JSON file (02a5064ed599d8f506774d7264207446a36cb751)

data/prompts-test.txt.gz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c2e72704d07041077a2a11b42be0128ecae8c33b5976305f2ea38b96297bcf9b
+size 19684

data/prompts-train.txt.gz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7923c99472c1a088a61c0c7812bbd8f9560dfe723765d18e24537d79c19e726a
+size 344941

data/vivos.tar.gz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:147477f7a7702cbafc2ee3808d1c142989d0dbc8d9fce8e07d5f329d5119e4ca
+size 1474408300

dataset_infos.json

@@ -1 +0,0 @@
-{"default": {"description": "VIVOS is a free Vietnamese speech corpus consisting of 15 hours of recording speech prepared for\nVietnamese Automatic Speech Recognition task.\nThe corpus was prepared by AILAB, a computer science lab of VNUHCM - University of Science, with Prof. Vu Hai Quan is the head of.\nWe publish this corpus in hope to attract more scientists to solve Vietnamese speech recognition problems.\n", "citation": "@inproceedings{luong-vu-2016-non,\n    title = \"A non-expert {K}aldi recipe for {V}ietnamese Speech Recognition System\",\n    author = \"Luong, Hieu-Thi  and\n      Vu, Hai-Quan\",\n    booktitle = \"Proceedings of the Third International Workshop on Worldwide Language Service Infrastructure and Second Workshop on Open Infrastructures and Analysis Frameworks for Human Language Technologies ({WLSI}/{OIAF}4{HLT}2016)\",\n    month = dec,\n    year = \"2016\",\n    address = \"Osaka, Japan\",\n    publisher = \"The COLING 2016 Organizing Committee\",\n    url = \"https://aclanthology.org/W16-5207\",\n    pages = \"51--55\",\n}\n", "homepage": "https://doi.org/10.5281/zenodo.7068130", "license": "CC BY-NC-SA 4.0", "features": {"speaker_id": {"dtype": "string", "id": null, "_type": "Value"}, "path": {"dtype": "string", "id": null, "_type": "Value"}, "audio": {"sampling_rate": 16000, "mono": true, "decode": true, "id": null, "_type": "Audio"}, "sentence": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "vivos", "config_name": "default", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 1722002133, "num_examples": 11660, "dataset_name": "vivos"}, "test": {"name": "test", "num_bytes": 86120227, "num_examples": 760, "dataset_name": "vivos"}}, "download_checksums": {"https://s3.amazonaws.com/datasets.huggingface.co/vivos/train/prompts.txt": {"num_bytes": 1075754, "checksum": "d6c6fcbe258d80d0f63e0f87d414b805f6ae11f41d40cdba5454152c3d6f14c0"}, "https://s3.amazonaws.com/datasets.huggingface.co/vivos/test/prompts.txt": {"num_bytes": 56446, "checksum": "ed27898d081eaa41b1e7e38451eb85f7ca06138896b471691510e7bab1187c2e"}, "https://zenodo.org/record/7068130/files/vivos.tar.gz": {"num_bytes": 1474408300, "checksum": "147477f7a7702cbafc2ee3808d1c142989d0dbc8d9fce8e07d5f329d5119e4ca"}}, "download_size": 1475540500, "post_processing_size": null, "dataset_size": 1808122360, "size_in_bytes": 3283662860}}

vivos.py

@@ -42,11 +42,12 @@ _HOMEPAGE = "https://doi.org/10.5281/zenodo.7068130"
 
 _LICENSE = "CC BY-NC-SA 4.0"
 
+# Source data: "https://zenodo.org/record/7068130/files/vivos.tar.gz"
 _DATA_URL = "https://zenodo.org/record/7068130/files/vivos.tar.gz"
 
 _PROMPTS_URLS = {
-    "train": "https://s3.amazonaws.com/datasets.huggingface.co/vivos/train/prompts.txt",
-    "test": "https://s3.amazonaws.com/datasets.huggingface.co/vivos/test/prompts.txt",
+    "train": "data/prompts-train.txt.gz",
+    "test": "data/prompts-test.txt.gz",
 }
 
 
@@ -89,7 +90,7 @@ class VivosDataset(datasets.GeneratorBasedBuilder):
         # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLs
         # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
         # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
-        prompts_paths = dl_manager.download(_PROMPTS_URLS)
+        prompts_paths = dl_manager.download_and_extract(_PROMPTS_URLS)
         archive = dl_manager.download(_DATA_URL)
         train_dir = "vivos/train"
         test_dir = "vivos/test"