update link

.idea/custom_common_voice.iml

@@ -4,7 +4,7 @@
     <content url="file://$MODULE_DIR$">
       <excludeFolder url="file://$MODULE_DIR$/venv" />
     </content>
-    <orderEntry type="jdk" jdkName="Python 3.8 (custom_common_voice)" jdkType="Python SDK" />
+    <orderEntry type="inheritedJdk" />
     <orderEntry type="sourceFolder" forTests="false" />
   </component>
 </module>

README.md

@@ -1,202 +1,30 @@
 ---
-pretty_name: Common Voice
-annotations_creators:
-- crowdsourced
-language_creators:
+Pretty_name: Youtube Casual Audio
+
+Annotations_creators:
 - crowdsourced
-languages:
-- ab
-- ar
-- as
-- br
-- ca
-- cnh
-- cs
-- cv
-- cy
-- de
-- dv
-- el
-- en
-- eo
-- es
-- et
-- eu
-- fa
-- fi
-- fr
-- fy-NL
-- ga-IE
-- hi
-- hsb
-- hu
-- ia
-- id
-- it
-- ja
-- ka
-- kab
-- ky
-- lg
-- lt
-- lv
-- mn
-- mt
-- nl
-- or
-- pa-IN
-- pl
-- pt
-- rm-sursilv
-- rm-vallader
-- ro
-- ru
-- rw
-- sah
-- sl
-- sv-SE
-- ta
-- th
-- tr
-- tt
-- uk
+
+Language_creators:
+- datlq
+
+Languages:
 - vi
-- vot
-- zh-CN
-- zh-HK
-- zh-TW
-licenses:
+
+Licenses:
 - cc0-1.0
+
 multilinguality:
-- multilingual
-size_categories:
-  ab:
-  - n<1K
-  ar:
-  - 10K<n<100K
-  as:
-  - n<1K
-  br:
-  - 10K<n<100K
-  ca:
-  - 100K<n<1M
-  cnh:
-  - 1K<n<10K
-  cs:
-  - 10K<n<100K
-  cv:
-  - 10K<n<100K
-  cy:
-  - 10K<n<100K
-  de:
-  - 100K<n<1M
-  dv:
-  - 1K<n<10K
-  el:
-  - 10K<n<100K
-  en:
-  - 100K<n<1M
-  eo:
-  - 10K<n<100K
-  es:
-  - 100K<n<1M
-  et:
-  - 10K<n<100K
-  eu:
-  - 10K<n<100K
-  fa:
-  - 10K<n<100K
-  fi:
-  - 1K<n<10K
-  fr:
-  - 100K<n<1M
-  fy-NL:
-  - 10K<n<100K
-  ga-IE:
-  - 1K<n<10K
-  hi:
-  - n<1K
-  hsb:
-  - 1K<n<10K
-  hu:
-  - 1K<n<10K
-  ia:
-  - 1K<n<10K
-  id:
-  - 10K<n<100K
-  it:
-  - 100K<n<1M
-  ja:
-  - 1K<n<10K
-  ka:
-  - 1K<n<10K
-  kab:
-  - 100K<n<1M
-  ky:
-  - 10K<n<100K
-  lg:
-  - 1K<n<10K
-  lt:
-  - 1K<n<10K
-  lv:
-  - 1K<n<10K
-  mn:
-  - 1K<n<10K
-  mt:
-  - 10K<n<100K
-  nl:
-  - 10K<n<100K
-  or:
-  - 1K<n<10K
-  pa-IN:
-  - 1K<n<10K
-  pl:
-  - 10K<n<100K
-  pt:
-  - 10K<n<100K
-  rm-sursilv:
-  - 1K<n<10K
-  rm-vallader:
-  - 1K<n<10K
-  ro:
-  - 1K<n<10K
-  ru:
-  - 10K<n<100K
-  rw:
-  - 100K<n<1M
-  sah:
-  - 1K<n<10K
-  sl:
-  - 1K<n<10K
-  sv-SE:
-  - 1K<n<10K
-  ta:
-  - 10K<n<100K
-  th:
-  - 10K<n<100K
-  tr:
-  - 1K<n<10K
-  tt:
-  - 10K<n<100K
-  uk:
-  - 10K<n<100K
   vi:
-  - 1K<n<10K
-  vot:
-  - n<1K
-  zh-CN:
-  - 10K<n<100K
-  zh-HK:
-  - 10K<n<100K
-  zh-TW:
-  - 10K<n<100K
+  - 190K<n<200K
+
 source_datasets:
-- extended|common_voice
+- extended|youtube
+
 task_categories:
 - speech-processing
+
 task_ids:
 - automatic-speech-recognition
-paperswithcode_id: common-voice
 ---
 
 # Dataset Card for common_voice
@@ -227,17 +55,15 @@ paperswithcode_id: common-voice
 
 ## Dataset Description
 
-- **Homepage:** https://commonvoice.mozilla.org/en/datasets
-- **Repository:** https://github.com/common-voice/common-voice
-- **Paper:** https://commonvoice.mozilla.org/en/datasets
+- **Homepage:** [Needs More Information]
+- **Repository:** [Needs More Information]
+- **Paper:** [Needs More Information]
 - **Leaderboard:** [Needs More Information]
 - **Point of Contact:** [Needs More Information]
 
 ### Dataset Summary
 
-The Common Voice dataset consists of a unique MP3 and corresponding text file. Many of the 9,283 recorded hours in the dataset also include demographic metadata like age, sex, and accent that can help train the accuracy of speech recognition engines.
-
-The dataset currently consists of 7,335 validated hours in 60 languages, but were always adding more voices and languages. Take a look at our Languages page to request a language or start contributing.
+[Needs More Information]
 
 ### Supported Tasks and Leaderboards
 
@@ -245,7 +71,7 @@ The dataset currently consists of 7,335 validated hours in 60 languages, but we
 
 ### Languages
 
-English
+Vietnamese
 
 ## Dataset Structure
 
@@ -254,47 +80,27 @@ English
 A typical data point comprises the path to the audio file, called path and its sentence. Additional fields include accent, age, client_id, up_votes down_votes, gender, locale and segment.
 
 `
-{'accent': 'netherlands', 'age': 'fourties', 'client_id': 'bbbcb732e0f422150c30ff3654bbab572e2a617da107bca22ff8b89ab2e4f124d03b6a92c48322862f60bd0179ae07baf0f9b4f9c4e11d581e0cec70f703ba54', 'down_votes': 0, 'gender': 'male', 'locale': 'nl', 'path': 'nl/clips/common_voice_nl_23522441.mp3', 'segment': "''", 'sentence': 'Ik vind dat een dubieuze procedure.', 'up_votes': 2, 'audio': {'path': `nl/clips/common_voice_nl_23522441.mp3', 'array': array([-0.00048828, -0.00018311, -0.00137329, ...,  0.00079346, 0.00091553,  0.00085449], dtype=float32), 'sampling_rate': 48000}
+{
+'file_path': 'audio/_1OsFqkFI38_34.304_39.424.wav', 
+'script': 'Ik vind dat een dubieuze procedure.', 
+'audio': {'path': 'audio/_1OsFqkFI38_34.304_39.424.wav', 
+          'array': array([-0.00048828, -0.00018311, -0.00137329, ...,  0.00079346, 0.00091553,  0.00085449], dtype=float32), 
+          'sampling_rate': 16000}
 `
 
 ### Data Fields
 
-client_id: An id for which client (voice) made the recording
-
-path: The path to the audio file
+file_path: The path to the audio file
 
 audio: A dictionary containing the path to the downloaded audio file, the decoded audio array, and the sampling rate. Note that when accessing the audio column: `dataset[0]["audio"]` the audio file is automatically decoded and resampled to `dataset.features["audio"].sampling_rate`. Decoding and resampling of a large number of audio files might take a significant amount of time. Thus it is important to first query the sample index before the `"audio"` column, *i.e.* `dataset[0]["audio"]` should **always** be preferred over `dataset["audio"][0]`.
 
-sentence: The sentence the user was prompted to speak
-
-up_votes: How many upvotes the audio file has received from reviewers
-
-down_votes: How many downvotes the audio file has received from reviewers
-
-age: The age of the speaker.
-
-gender: The gender of the speaker
-
-accent: Accent of the speaker
-
-locale: The locale of the speaker
-
-segment: Usually empty field
+script: The sentence the user was prompted to speak
 
 ### Data Splits
 
-The speech material has been subdivided into portions for dev, train, test, validated, invalidated, reported and other.
-
-The validated data is data that has been validated with reviewers and recieved upvotes that the data is of high quality.
-
-The invalidated data is data has been invalidated by reviewers
-and recieved downvotes that the data is of low quality.
+The speech material has been subdivided into portions for train, test, validated.
 
-The reported data is data that has been reported, for different reasons.
-
-The other data is data that has not yet been reviewed.
-
-The dev, test, train are all data that has been reviewed, deemed of high quality and split into dev, test and train.
+The val, test, train are all data that has been reviewed, deemed of high quality and split into val, test and train.
 
 ## Dataset Creation
 
@@ -324,13 +130,13 @@ The dev, test, train are all data that has been reviewed, deemed of high quality
 
 ### Personal and Sensitive Information
 
-The dataset consists of people who have donated their voice online.  You agree to not attempt to determine the identity of speakers in the Common Voice dataset.
+[Needs More Information]
 
 ## Considerations for Using the Data
 
 ### Social Impact of Dataset
 
-The dataset consists of people who have donated their voice online.  You agree to not attempt to determine the identity of speakers in the Common Voice dataset.
+[Needs More Information]
 
 ### Discussion of Biases
 
@@ -348,20 +154,12 @@ The dataset consists of people who have donated their voice online.  You agree t
 
 ### Licensing Information
 
-Public Domain, [CC-0](https://creativecommons.org/share-your-work/public-domain/cc0/)
+[Needs More Information]
 
 ### Citation Information
 
-```
-@inproceedings{commonvoice:2020,
-  author = {Ardila, R. and Branson, M. and Davis, K. and Henretty, M. and Kohler, M. and Meyer, J. and Morais, R. and Saunders, L. and Tyers, F. M. and Weber, G.},
-  title = {Common Voice: A Massively-Multilingual Speech Corpus},
-  booktitle = {Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020)},
-  pages = {4211--4215},
-  year = 2020
-}
-```
+[Needs More Information]
 
 ### Contributions
 
-Thanks to [@BirgerMoell](https://github.com/BirgerMoell) for adding this dataset.
+Thanks to [@datlq](https://github.com/datlq98) for adding this dataset.

dataset_infos.json

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:6474db188c1ee3b46ac983c0c6febbe0598953626075303f567210caf11cde2c
-size 1659
+oid sha256:04c7ab7fce049fbadb625937bd5594f09763621100cf5ad7601850795f702654
+size 1081

custom_common_voice.py → youtube_casual_audio.py

@@ -21,25 +21,22 @@ import pandas as pd
 import re
 
 
-_DATA_URL = "https://dutudn-my.sharepoint.com/:u:/g/personal/122180028_sv1_dut_udn_vn/EYsBHQzK4JVFhmN50e5vRFMBizbGJGXe_HlxV9uRlLaTyg?e=s1czWW?download=1"
+_DATA_URL = "https://dutudn-my.sharepoint.com/:u:/g/personal/122180028_sv1_dut_udn_vn/Ed5mI5CjXIxHgb2qqPOElj0BBgn7FGT75SUgPdIuMS1LDw?download=1"
 _PROMPTS_URLS = {
-    "train": "https://drive.google.com/uc?export=download&id=13sANpjVoF9FIXj_rGGNvVNuK0GscPVsW",
-    "test": "https://drive.google.com/uc?export=download&id=173oUWFMbeFUBnfoVke4dH2fiHdgOu9xb",
-    "validation": "https://drive.google.com/uc?export=download&id=1J1zTG0IMPIRWnnw3dyr2UTyiq-KvlcX5"
+    "train": "https://drive.google.com/uc?export=download&id=1s5d-1ZTzcxsnxUjiBLsv9KCB-yBcXyQ9",
+    "test": "https://drive.google.com/uc?export=download&id=1-l1QdNQ98DGZM63-GOKIVnFvxTz2SGeK",
+    "validation": "https://drive.google.com/uc?export=download&id=1GM_6s5icko6zRrldx8LcbANyl0geMSl8"
 }
 
 _DESCRIPTION = """\
-Common Voice is Mozilla's initiative to help teach machines how real people speak.
-The dataset currently consists of 7,335 validated hours of speech in 60 languages, but we’re always adding more voices
- and languages.
 """
 
 _LANGUAGES = {
     "vi": {
         "Language": "Vietnamese",
-        "Date": "2020-12-11",
-        "Size": "50 MB",
-        "Version": "vi_1h_2020-12-11",
+        "Date": "2021-12-11",
+        "Size": "17000 MB",
+        "Version": "vi_100h_2020-12-11",
         "Validated_Hr_Total": 0.74,
         "Overall_Hr_Total": 1,
         "Number_Of_Voice": 62,
@@ -83,11 +80,6 @@ class CustomCommonVoice(datasets.GeneratorBasedBuilder):
             name=lang_id,
             language=_LANGUAGES[lang_id]["Language"],
             sub_version=_LANGUAGES[lang_id]["Version"],
-            # date=_LANGUAGES[lang_id]["Date"],
-            # size=_LANGUAGES[lang_id]["Size"],
-            # val_hrs=_LANGUAGES[lang_id]["Validated_Hr_Total"],
-            # total_hrs=_LANGUAGES[lang_id]["Overall_Hr_Total"],
-            # num_of_voice=_LANGUAGES[lang_id]["Number_Of_Voice"],
         )
         for lang_id in _LANGUAGES.keys()
     ]
@@ -115,8 +107,7 @@ class CustomCommonVoice(datasets.GeneratorBasedBuilder):
         """Returns SplitGenerators."""
         archive = dl_manager.download(_DATA_URL)
         tsv_files = dl_manager.download(_PROMPTS_URLS)
-        path_to_data = "content/data_2/"
-        path_to_clips = path_to_data + "audio"
+        path_to_data = "audio"
 
         return [
             datasets.SplitGenerator(
@@ -124,7 +115,7 @@ class CustomCommonVoice(datasets.GeneratorBasedBuilder):
                 gen_kwargs={
                     "tsv_files": tsv_files["train"],
                     "audio_files": dl_manager.iter_archive(archive),
-                    "path_to_clips": path_to_clips,
+                    "path_to_clips": path_to_data,
                 },
             ),
             datasets.SplitGenerator(
@@ -132,7 +123,7 @@ class CustomCommonVoice(datasets.GeneratorBasedBuilder):
                 gen_kwargs={
                     "tsv_files": tsv_files["test"],
                     "audio_files": dl_manager.iter_archive(archive),
-                    "path_to_clips": path_to_clips,
+                    "path_to_clips": path_to_data,
                 },
             ),
             datasets.SplitGenerator(
@@ -140,25 +131,9 @@ class CustomCommonVoice(datasets.GeneratorBasedBuilder):
                 gen_kwargs={
                     "tsv_files": tsv_files["validation"],
                     "audio_files": dl_manager.iter_archive(archive),
-                    "path_to_clips": path_to_clips,
+                    "path_to_clips": path_to_data,
                 },
             ),
-            # datasets.SplitGenerator(
-            #     name="other",
-            #     gen_kwargs={
-            #         "files": dl_manager.iter_archive(archive),
-            #         "filepath": "/".join([path_to_data, "other.tsv"]),
-            #         "path_to_clips": path_to_clips,
-            #     },
-            # ),
-            # datasets.SplitGenerator(
-            #     name="invalidated",
-            #     gen_kwargs={
-            #         "files": dl_manager.iter_archive(archive),
-            #         "filepath": "/".join([path_to_data, "invalidated.tsv"]),
-            #         "path_to_clips": path_to_clips,
-            #     },
-            # ),
         ]
 
     def _generate_examples(self, tsv_files, audio_files, path_to_clips):
@@ -190,49 +165,8 @@ class CustomCommonVoice(datasets.GeneratorBasedBuilder):
                 "duration": duration
             }
 
-        # inside_clips_dir = False
-
         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 path, {**examples[path], "audio": audio}
-            # elif "custom_common_voice.tsv" in path:
-            #     continue
-            # elif ".txt" in path:
-            #     continue
-            # elif inside_clips_dir:
-            #     break
-
-        # for path, f in tsv_files:
-        #     if path == filepath:
-        #         metadata_found = True
-        #         lines = f.readlines()
-        #         headline = lines[0]
-        #         column_names = headline.strip().split("\t")
-        #         assert (
-        #             column_names == data_fields
-        #         ), f"The file should have {data_fields} as column names, but has {column_names}"
-        #         for line in lines[1:]:
-        #             field_values = line.strip().split("\t")
-        #             # set full path for mp3 audio file
-        #             audio_path = path_to_clips + "/" + field_values[path_idx]
-        #             all_field_values[audio_path] = field_values
-        #     elif path.startswith(path_to_clips):
-        #         assert metadata_found, "Found audio clips before the metadata TSV file."
-        #         if not all_field_values:
-        #             break
-        #         if path in all_field_values:
-        #             field_values = all_field_values[path]
-        #
-        #             # if data is incomplete, fill with empty values
-        #             if len(field_values) < len(data_fields):
-        #                 field_values += (len(data_fields) - len(field_values)) * ["''"]
-        #
-        #             result = {key: value for key, value in zip(data_fields, field_values)}
-        #
-        #             # set audio feature
-        #             result["audio"] = {"path": path, "bytes": f.read()}
-        #
-        #             yield path, result