转换 common_voice_11_0 中的 ja 数据

.gitattributes

@@ -1,4 +1,5 @@
 *.7z filter=lfs diff=lfs merge=lfs -text
+*.tsv filter=lfs diff=lfs merge=lfs -text
 *.ipynb filter=lfs diff=lfs merge=lfs -text
 *.arrow filter=lfs diff=lfs merge=lfs -text
 *.avro filter=lfs diff=lfs merge=lfs -text

.gitignore

@@ -1,5 +1,9 @@
 # log and data files
-common_voice_11_0/
+# common_voice_11_0/
+common_voice_11_0/audio/
+common_voice_11_0/ja/
+data/common_voice_11_0/audio/
+data/common_voice_11_0/ja/
 Common Voice Scripted Speech 25.0 - Japanese/
 *.model
 *.pkl
@@ -132,7 +136,7 @@ env.bak/
 venv.bak/
 
 # VSCode project settins
-.vscode/
+# .vscode/
 
 # Spyder project settings
 .spyderproject

.vscode/launch.json

@@ -0,0 +1,12 @@
+{
+    "version": "0.2.0",
+    "configurations": [
+        {
+            "name": "Python Debugger: Current File",
+            "type": "debugpy",
+            "request": "launch",
+            "program": "${file}",
+            "console": "integratedTerminal"
+        }
+    ]
+}

convert_ja.py

@@ -27,7 +27,7 @@ def convert_ja():
         name="ja",
         ensure_ascii=False,
         use_auth_token=False,
-        num_proc=4,  # 使用多进程加快速度
+        num_proc=8,  # 使用多进程加快速度
     )
     
     # 转换为 OmegaConf

data/common_voice_11_0/.gitattributes

@@ -0,0 +1,53 @@
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.lz4 filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+# Audio files - uncompressed
+*.pcm filter=lfs diff=lfs merge=lfs -text
+*.sam filter=lfs diff=lfs merge=lfs -text
+*.raw filter=lfs diff=lfs merge=lfs -text
+# Audio files - compressed
+*.aac filter=lfs diff=lfs merge=lfs -text
+*.flac filter=lfs diff=lfs merge=lfs -text
+*.mp3 filter=lfs diff=lfs merge=lfs -text
+*.ogg filter=lfs diff=lfs merge=lfs -text
+*.wav filter=lfs diff=lfs merge=lfs -text
+# Image files - uncompressed
+*.bmp filter=lfs diff=lfs merge=lfs -text
+*.gif filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text
+*.tiff filter=lfs diff=lfs merge=lfs -text
+# Image files - compressed
+*.jpg filter=lfs diff=lfs merge=lfs -text
+*.jpeg filter=lfs diff=lfs merge=lfs -text
+*.webp filter=lfs diff=lfs merge=lfs -text
+*.tsv filter=lfs diff=lfs merge=lfs -text

data/common_voice_11_0/README.md

@@ -0,0 +1,589 @@
+---
+annotations_creators:
+- crowdsourced
+language_creators:
+- crowdsourced
+license:
+- cc0-1.0
+multilinguality:
+- multilingual
+size_categories:
+  ab:
+  - 10K<n<100K
+  ar:
+  - 100K<n<1M
+  as:
+  - 1K<n<10K
+  ast:
+  - n<1K
+  az:
+  - n<1K
+  ba:
+  - 100K<n<1M
+  bas:
+  - 1K<n<10K
+  be:
+  - 100K<n<1M
+  bg:
+  - 1K<n<10K
+  bn:
+  - 100K<n<1M
+  br:
+  - 10K<n<100K
+  ca:
+  - 1M<n<10M
+  ckb:
+  - 100K<n<1M
+  cnh:
+  - 1K<n<10K
+  cs:
+  - 10K<n<100K
+  cv:
+  - 10K<n<100K
+  cy:
+  - 100K<n<1M
+  da:
+  - 1K<n<10K
+  de:
+  - 100K<n<1M
+  dv:
+  - 10K<n<100K
+  el:
+  - 10K<n<100K
+  en:
+  - 1M<n<10M
+  eo:
+  - 1M<n<10M
+  es:
+  - 1M<n<10M
+  et:
+  - 10K<n<100K
+  eu:
+  - 100K<n<1M
+  fa:
+  - 100K<n<1M
+  fi:
+  - 10K<n<100K
+  fr:
+  - 100K<n<1M
+  fy-NL:
+  - 10K<n<100K
+  ga-IE:
+  - 1K<n<10K
+  gl:
+  - 10K<n<100K
+  gn:
+  - 1K<n<10K
+  ha:
+  - 1K<n<10K
+  hi:
+  - 10K<n<100K
+  hsb:
+  - 1K<n<10K
+  hu:
+  - 10K<n<100K
+  hy-AM:
+  - 1K<n<10K
+  ia:
+  - 10K<n<100K
+  id:
+  - 10K<n<100K
+  ig:
+  - 1K<n<10K
+  it:
+  - 100K<n<1M
+  ja:
+  - 10K<n<100K
+  ka:
+  - 10K<n<100K
+  kab:
+  - 100K<n<1M
+  kk:
+  - 1K<n<10K
+  kmr:
+  - 10K<n<100K
+  ky:
+  - 10K<n<100K
+  lg:
+  - 100K<n<1M
+  lt:
+  - 10K<n<100K
+  lv:
+  - 1K<n<10K
+  mdf:
+  - n<1K
+  mhr:
+  - 100K<n<1M
+  mk:
+  - n<1K
+  ml:
+  - 1K<n<10K
+  mn:
+  - 10K<n<100K
+  mr:
+  - 10K<n<100K
+  mrj:
+  - 10K<n<100K
+  mt:
+  - 10K<n<100K
+  myv:
+  - 1K<n<10K
+  nan-tw:
+  - 10K<n<100K
+  ne-NP:
+  - n<1K
+  nl:
+  - 10K<n<100K
+  nn-NO:
+  - n<1K
+  or:
+  - 1K<n<10K
+  pa-IN:
+  - 1K<n<10K
+  pl:
+  - 100K<n<1M
+  pt:
+  - 100K<n<1M
+  rm-sursilv:
+  - 1K<n<10K
+  rm-vallader:
+  - 1K<n<10K
+  ro:
+  - 10K<n<100K
+  ru:
+  - 100K<n<1M
+  rw:
+  - 1M<n<10M
+  sah:
+  - 1K<n<10K
+  sat:
+  - n<1K
+  sc:
+  - 1K<n<10K
+  sk:
+  - 10K<n<100K
+  skr:
+  - 1K<n<10K
+  sl:
+  - 10K<n<100K
+  sr:
+  - 1K<n<10K
+  sv-SE:
+  - 10K<n<100K
+  sw:
+  - 100K<n<1M
+  ta:
+  - 100K<n<1M
+  th:
+  - 100K<n<1M
+  ti:
+  - n<1K
+  tig:
+  - n<1K
+  tok:
+  - 1K<n<10K
+  tr:
+  - 10K<n<100K
+  tt:
+  - 10K<n<100K
+  tw:
+  - n<1K
+  ug:
+  - 10K<n<100K
+  uk:
+  - 10K<n<100K
+  ur:
+  - 100K<n<1M
+  uz:
+  - 100K<n<1M
+  vi:
+  - 10K<n<100K
+  vot:
+  - n<1K
+  yue:
+  - 10K<n<100K
+  zh-CN:
+  - 100K<n<1M
+  zh-HK:
+  - 100K<n<1M
+  zh-TW:
+  - 100K<n<1M
+source_datasets:
+- extended|common_voice
+task_categories:
+- automatic-speech-recognition
+task_ids: []
+paperswithcode_id: common-voice
+pretty_name: Common Voice Corpus 11.0
+language_bcp47:
+- ab
+- ar
+- as
+- ast
+- az
+- ba
+- bas
+- be
+- bg
+- bn
+- br
+- ca
+- ckb
+- cnh
+- cs
+- cv
+- cy
+- da
+- de
+- dv
+- el
+- en
+- eo
+- es
+- et
+- eu
+- fa
+- fi
+- fr
+- fy-NL
+- ga-IE
+- gl
+- gn
+- ha
+- hi
+- hsb
+- hu
+- hy-AM
+- ia
+- id
+- ig
+- it
+- ja
+- ka
+- kab
+- kk
+- kmr
+- ky
+- lg
+- lt
+- lv
+- mdf
+- mhr
+- mk
+- ml
+- mn
+- mr
+- mrj
+- mt
+- myv
+- nan-tw
+- ne-NP
+- nl
+- nn-NO
+- or
+- pa-IN
+- pl
+- pt
+- rm-sursilv
+- rm-vallader
+- ro
+- ru
+- rw
+- sah
+- sat
+- sc
+- sk
+- skr
+- sl
+- sr
+- sv-SE
+- sw
+- ta
+- th
+- ti
+- tig
+- tok
+- tr
+- tt
+- tw
+- ug
+- uk
+- ur
+- uz
+- vi
+- vot
+- yue
+- zh-CN
+- zh-HK
+- zh-TW
+extra_gated_prompt: By clicking on “Access repository” below, you also agree to not
+  attempt to determine the identity of speakers in the Common Voice dataset.
+---
+
+# Dataset Card for Common Voice Corpus 11.0
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+  - [How to use](#how-to-use)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-fields)
+  - [Data Splits](#data-splits)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+  - [Contributions](#contributions)
+
+## Dataset Description
+
+- **Homepage:** https://commonvoice.mozilla.org/en/datasets
+- **Repository:** https://github.com/common-voice/common-voice
+- **Paper:** https://arxiv.org/abs/1912.06670
+- **Leaderboard:** https://paperswithcode.com/dataset/common-voice
+- **Point of Contact:** [Anton Lozhkov](mailto:anton@huggingface.co)
+
+### Dataset Summary
+
+The Common Voice dataset consists of a unique MP3 and corresponding text file. 
+Many of the 24210 recorded hours in the dataset also include demographic metadata like age, sex, and accent 
+that can help improve the accuracy of speech recognition engines.
+
+The dataset currently consists of 16413 validated hours in 100 languages, but more voices and languages are always added. 
+Take a look at the [Languages](https://commonvoice.mozilla.org/en/languages) page to request a language or start contributing.
+
+### Supported Tasks and Leaderboards
+
+The results for models trained on the Common Voice datasets are available via the 
+[🤗 Autoevaluate Leaderboard](https://huggingface.co/spaces/autoevaluate/leaderboards?dataset=mozilla-foundation%2Fcommon_voice_11_0&only_verified=0&task=automatic-speech-recognition&config=ar&split=test&metric=wer)
+
+### Languages
+
+```
+Abkhaz, Arabic, Armenian, Assamese, Asturian, Azerbaijani, Basaa, Bashkir, Basque, Belarusian, Bengali, Breton, Bulgarian, Cantonese, Catalan, Central Kurdish, Chinese (China), Chinese (Hong Kong), Chinese (Taiwan), Chuvash, Czech, Danish, Dhivehi, Dutch, English, Erzya, Esperanto, Estonian, Finnish, French, Frisian, Galician, Georgian, German, Greek, Guarani, Hakha Chin, Hausa, Hill Mari, Hindi, Hungarian, Igbo, Indonesian, Interlingua, Irish, Italian, Japanese, Kabyle, Kazakh, Kinyarwanda, Kurmanji Kurdish, Kyrgyz, Latvian, Lithuanian, Luganda, Macedonian, Malayalam, Maltese, Marathi, Meadow Mari, Moksha, Mongolian, Nepali, Norwegian Nynorsk, Odia, Persian, Polish, Portuguese, Punjabi, Romanian, Romansh Sursilvan, Romansh Vallader, Russian, Sakha, Santali (Ol Chiki), Saraiki, Sardinian, Serbian, Slovak, Slovenian, Sorbian, Upper, Spanish, Swahili, Swedish, Taiwanese (Minnan), Tamil, Tatar, Thai, Tigre, Tigrinya, Toki Pona, Turkish, Twi, Ukrainian, Urdu, Uyghur, Uzbek, Vietnamese, Votic, Welsh
+```
+
+## How to use
+
+The `datasets` library allows you to load and pre-process your dataset in pure Python, at scale. The dataset can be downloaded and prepared in one call to your local drive by using the `load_dataset` function. 
+
+For example, to download the Hindi config, simply specify the corresponding language config name (i.e., "hi" for Hindi):
+```python
+from datasets import load_dataset
+
+cv_11 = load_dataset("mozilla-foundation/common_voice_11_0", "hi", split="train")
+```
+
+Using the datasets library, you can also stream the dataset on-the-fly by adding a `streaming=True` argument to the `load_dataset` function call. Loading a dataset in streaming mode loads individual samples of the dataset at a time, rather than downloading the entire dataset to disk.
+```python
+from datasets import load_dataset
+
+cv_11 = load_dataset("mozilla-foundation/common_voice_11_0", "hi", split="train", streaming=True)
+
+print(next(iter(cv_11)))
+```
+
+*Bonus*: create a [PyTorch dataloader](https://huggingface.co/docs/datasets/use_with_pytorch) directly with your own datasets (local/streamed).
+
+### Local
+
+```python
+from datasets import load_dataset
+from torch.utils.data.sampler import BatchSampler, RandomSampler
+
+cv_11 = load_dataset("mozilla-foundation/common_voice_11_0", "hi", split="train")
+batch_sampler = BatchSampler(RandomSampler(cv_11), batch_size=32, drop_last=False)
+dataloader = DataLoader(cv_11, batch_sampler=batch_sampler)
+```
+
+### Streaming
+
+```python
+from datasets import load_dataset
+from torch.utils.data import DataLoader
+
+cv_11 = load_dataset("mozilla-foundation/common_voice_11_0", "hi", split="train")
+dataloader = DataLoader(cv_11, batch_size=32)
+```
+
+To find out more about loading and preparing audio datasets, head over to [hf.co/blog/audio-datasets](https://huggingface.co/blog/audio-datasets).
+
+### Example scripts
+
+Train your own CTC or Seq2Seq Automatic Speech Recognition models on Common Voice 11 with `transformers` - [here](https://github.com/huggingface/transformers/tree/main/examples/pytorch/speech-recognition).
+
+## Dataset Structure
+
+### Data Instances
+
+A typical data point comprises the `path` to the audio file and its `sentence`. 
+Additional fields include `accent`, `age`, `client_id`, `up_votes`, `down_votes`, `gender`, `locale` and `segment`.
+
+```python
+{
+  'client_id': 'd59478fbc1ee646a28a3c652a119379939123784d99131b865a89f8b21c81f69276c48bd574b81267d9d1a77b83b43e6d475a6cfc79c232ddbca946ae9c7afc5', 
+  'path': 'et/clips/common_voice_et_18318995.mp3', 
+  'audio': {
+    'path': 'et/clips/common_voice_et_18318995.mp3', 
+    'array': array([-0.00048828, -0.00018311, -0.00137329, ...,  0.00079346, 0.00091553,  0.00085449], dtype=float32), 
+    'sampling_rate': 48000
+  }, 
+  'sentence': 'Tasub kokku saada inimestega, keda tunned juba ammust ajast saati.', 
+  'up_votes': 2, 
+  'down_votes': 0, 
+  'age': 'twenties', 
+  'gender': 'male', 
+  'accent': '', 
+  'locale': 'et', 
+  'segment': ''
+}
+```
+
+### Data Fields
+
+`client_id` (`string`): An id for which client (voice) made the recording
+
+`path` (`string`): The path to the audio file
+
+`audio` (`dict`): 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` (`string`): The sentence the user was prompted to speak
+
+`up_votes` (`int64`): How many upvotes the audio file has received from reviewers
+
+`down_votes` (`int64`): How many downvotes the audio file has received from reviewers
+
+`age` (`string`): The age of the speaker (e.g. `teens`, `twenties`, `fifties`)
+
+`gender` (`string`): The gender of the speaker
+
+`accent` (`string`): Accent of the speaker
+
+`locale` (`string`): The locale of the speaker
+
+`segment` (`string`): Usually an empty field
+
+### 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 received upvotes that the data is of high quality.
+
+The invalidated data is data has been invalidated by reviewers
+and received downvotes indicating that the data is of low quality.
+
+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.
+
+## Data Preprocessing Recommended by Hugging Face
+
+The following are data preprocessing steps advised by the Hugging Face team. They are accompanied by an example code snippet that shows how to put them to practice. 
+
+Many examples in this dataset have trailing quotations marks, e.g _“the cat sat on the mat.“_. These trailing quotation marks do not change the actual meaning of the sentence, and it is near impossible to infer whether a sentence is a quotation or not a quotation from audio data alone. In these cases, it is advised to strip the quotation marks, leaving: _the cat sat on the mat_.
+
+In addition, the majority of training sentences end in punctuation ( . or ? or ! ), whereas just a small proportion do not. In the dev set, **almost all** sentences end in punctuation. Thus, it is recommended to append a full-stop ( . ) to the end of the small number of training examples that do not end in punctuation.
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("mozilla-foundation/common_voice_11_0", "en", use_auth_token=True)
+
+def prepare_dataset(batch):
+  """Function to preprocess the dataset with the .map method"""
+  transcription = batch["sentence"]
+  
+  if transcription.startswith('"') and transcription.endswith('"'):
+    # we can remove trailing quotation marks as they do not affect the transcription
+    transcription = transcription[1:-1]
+  
+  if transcription[-1] not in [".", "?", "!"]:
+    # append a full-stop to sentences that do not end in punctuation
+    transcription = transcription + "."
+  
+  batch["sentence"] = transcription
+  
+  return batch
+
+ds = ds.map(prepare_dataset, desc="preprocess dataset")
+```
+
+## Dataset Creation
+
+### Curation Rationale
+
+[Needs More Information]
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+[Needs More Information]
+
+#### Who are the source language producers?
+
+[Needs More Information]
+
+### Annotations
+
+#### Annotation process
+
+[Needs More Information]
+
+#### Who are the annotators?
+
+[Needs More Information]
+
+### 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.
+
+## 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.
+
+### Discussion of Biases
+
+[More Information Needed] 
+
+### Other Known Limitations
+
+[More Information Needed] 
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed] 
+
+### Licensing Information
+
+Public Domain, [CC-0](https://creativecommons.org/share-your-work/public-domain/cc0/)
+
+### 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
+}
+```

data/common_voice_11_0/common_voice_11_0.py

@@ -0,0 +1,196 @@
+# coding=utf-8
+# Copyright 2022 The HuggingFace Datasets Authors and the current dataset script contributor.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+""" Common Voice Dataset"""
+
+
+import csv
+import os
+import json
+
+import datasets
+from datasets.utils.py_utils import size_str
+from tqdm import tqdm
+
+from .languages import LANGUAGES
+from .release_stats import STATS
+
+
+_CITATION = """\
+@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
+}
+"""
+
+_HOMEPAGE = "https://commonvoice.mozilla.org/en/datasets"
+
+_LICENSE = "https://creativecommons.org/publicdomain/zero/1.0/"
+
+_BASE_DIR = r"E:\huggingface_echodict\NeMo\data\common_voice_11_0"
+
+_AUDIO_URL = os.path.join(_BASE_DIR, "audio", "{lang}", "{split}", "{lang}_{split}_{shard_idx}.tar")
+
+_TRANSCRIPT_URL = os.path.join(_BASE_DIR, "transcript", "{lang}", "{split}.tsv")
+
+_N_SHARDS_URL = os.path.join(_BASE_DIR, "n_shards.json")
+
+
+class CommonVoiceConfig(datasets.BuilderConfig):
+    """BuilderConfig for CommonVoice."""
+
+    def __init__(self, name, version, **kwargs):
+        self.language = kwargs.pop("language", None)
+        self.release_date = kwargs.pop("release_date", None)
+        self.num_clips = kwargs.pop("num_clips", None)
+        self.num_speakers = kwargs.pop("num_speakers", None)
+        self.validated_hr = kwargs.pop("validated_hr", None)
+        self.total_hr = kwargs.pop("total_hr", None)
+        self.size_bytes = kwargs.pop("size_bytes", None)
+        self.size_human = size_str(self.size_bytes)
+        description = (
+            f"Common Voice speech to text dataset in {self.language} released on {self.release_date}. "
+            f"The dataset comprises {self.validated_hr} hours of validated transcribed speech data "
+            f"out of {self.total_hr} hours in total from {self.num_speakers} speakers. "
+            f"The dataset contains {self.num_clips} audio clips and has a size of {self.size_human}."
+        )
+        super(CommonVoiceConfig, self).__init__(
+            name=name,
+            version=datasets.Version(version),
+            description=description,
+            **kwargs,
+        )
+
+
+class CommonVoice(datasets.GeneratorBasedBuilder):
+    DEFAULT_WRITER_BATCH_SIZE = 1000
+
+    BUILDER_CONFIGS = [
+        CommonVoiceConfig(
+            name=lang,
+            version=STATS["version"],
+            language=LANGUAGES[lang],
+            release_date=STATS["date"],
+            num_clips=lang_stats["clips"],
+            num_speakers=lang_stats["users"],
+            validated_hr=float(lang_stats["validHrs"]) if lang_stats["validHrs"] else None,
+            total_hr=float(lang_stats["totalHrs"]) if lang_stats["totalHrs"] else None,
+            size_bytes=int(lang_stats["size"]) if lang_stats["size"] else None,
+        )
+        for lang, lang_stats in STATS["locales"].items()
+    ]
+
+    def _info(self):
+        total_languages = len(STATS["locales"])
+        total_valid_hours = STATS["totalValidHrs"]
+        description = (
+            "Common Voice is Mozilla's initiative to help teach machines how real people speak. "
+            f"The dataset currently consists of {total_valid_hours} validated hours of speech "
+            f" in {total_languages} languages, but more voices and languages are always added."
+        )
+        features = datasets.Features(
+            {
+                "client_id": datasets.Value("string"),
+                "path": datasets.Value("string"),
+                "audio": datasets.features.Audio(sampling_rate=48_000),
+                "sentence": datasets.Value("string"),
+                "up_votes": datasets.Value("int64"),
+                "down_votes": datasets.Value("int64"),
+                "age": datasets.Value("string"),
+                "gender": datasets.Value("string"),
+                "accent": datasets.Value("string"),
+                "locale": datasets.Value("string"),
+                "segment": datasets.Value("string"),
+            }
+        )
+
+        return datasets.DatasetInfo(
+            description=description,
+            features=features,
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+            version=self.config.version,
+        )
+
+    def _split_generators(self, dl_manager):
+        lang = self.config.name
+        n_shards_path = dl_manager.download_and_extract(_N_SHARDS_URL)
+        with open(n_shards_path, encoding="utf-8") as f:
+            n_shards = json.load(f)
+
+        audio_urls = {}
+        splits = ("train", "dev", "test", "other", "invalidated")
+        for split in splits:
+            audio_urls[split] = [
+                _AUDIO_URL.format(lang=lang, split=split, shard_idx=i) for i in range(n_shards[lang][split])
+            ]
+        archive_paths = dl_manager.download(audio_urls)
+        local_extracted_archive_paths = dl_manager.extract(archive_paths) if not dl_manager.is_streaming else {}
+
+        meta_urls = {split: _TRANSCRIPT_URL.format(lang=lang, split=split) for split in splits}
+        meta_paths = dl_manager.download_and_extract(meta_urls)
+
+        split_generators = []
+        split_names = {
+            "train": datasets.Split.TRAIN,
+            "dev": datasets.Split.VALIDATION,
+            "test": datasets.Split.TEST,
+        }
+        for split in splits:
+            split_generators.append(
+                datasets.SplitGenerator(
+                    name=split_names.get(split, split),
+                    gen_kwargs={
+                        "local_extracted_archive_paths": local_extracted_archive_paths.get(split),
+                        "archives": [dl_manager.iter_archive(path) for path in archive_paths.get(split)],
+                        "meta_path": meta_paths[split],
+                    },
+                ),
+            )
+
+        return split_generators
+
+    def _generate_examples(self, local_extracted_archive_paths, archives, meta_path):
+        data_fields = list(self._info().features.keys())
+        metadata = {}
+        with open(meta_path, encoding="utf-8") as f:
+            reader = csv.DictReader(f, delimiter="\t", quoting=csv.QUOTE_NONE)
+            for row in tqdm(reader, desc="Reading metadata..."):
+                if not row["path"].endswith(".mp3"):
+                    row["path"] += ".mp3"
+                # accent -> accents in CV 8.0
+                if "accents" in row:
+                    row["accent"] = row["accents"]
+                    del row["accents"]
+                # if data is incomplete, fill with empty values
+                for field in data_fields:
+                    if field not in row:
+                        row[field] = ""
+                metadata[row["path"]] = row
+
+        for i, audio_archive in enumerate(archives):
+            for path, file in audio_archive:
+                _, filename = os.path.split(path)
+                if filename in metadata:
+                    result = dict(metadata[filename])
+                    # set the audio feature and the path to the extracted file
+                    path = os.path.join(local_extracted_archive_paths[i], path) if local_extracted_archive_paths else path
+                    result["audio"] = {"path": path, "bytes": file.read()}
+                    result["path"] = path
+                    yield path, result

data/common_voice_11_0/count_n_shards.py

@@ -0,0 +1,22 @@
+from pathlib import Path
+import json
+
+
+splits = ["train", "dev", "test", "other", "invalidated"]
+
+if __name__ == "__main__":
+    n_files = {}
+    lang_dirs = [d for d in Path("audio").iterdir() if d.is_dir()]
+    for lang_dir in lang_dirs:
+        lang = lang_dir.name
+        n_files[lang] = {}
+        for split in splits:
+            split_dir = lang_dir / split
+            if split_dir.exists():
+                n_files_per_split = len(list(split_dir.glob("*.tar")))
+            else:
+                n_files_per_split = 0
+            n_files[lang][split] = n_files_per_split
+
+    with open("n_shards.json", "w") as f:
+        json.dump(dict(sorted(n_files.items(), key=lambda x: x[0])), f, ensure_ascii=False, indent=4)

data/common_voice_11_0/languages.py

@@ -0,0 +1 @@
+LANGUAGES = {'ab': 'Abkhaz', 'ace': 'Acehnese', 'ady': 'Adyghe', 'af': 'Afrikaans', 'am': 'Amharic', 'an': 'Aragonese', 'ar': 'Arabic', 'arn': 'Mapudungun', 'as': 'Assamese', 'ast': 'Asturian', 'az': 'Azerbaijani', 'ba': 'Bashkir', 'bas': 'Basaa', 'be': 'Belarusian', 'bg': 'Bulgarian', 'bn': 'Bengali', 'br': 'Breton', 'bs': 'Bosnian', 'bxr': 'Buryat', 'ca': 'Catalan', 'cak': 'Kaqchikel', 'ckb': 'Central Kurdish', 'cnh': 'Hakha Chin', 'co': 'Corsican', 'cs': 'Czech', 'cv': 'Chuvash', 'cy': 'Welsh', 'da': 'Danish', 'de': 'German', 'dsb': 'Sorbian, Lower', 'dv': 'Dhivehi', 'dyu': 'Dioula', 'el': 'Greek', 'en': 'English', 'eo': 'Esperanto', 'es': 'Spanish', 'et': 'Estonian', 'eu': 'Basque', 'fa': 'Persian', 'ff': 'Fulah', 'fi': 'Finnish', 'fo': 'Faroese', 'fr': 'French', 'fy-NL': 'Frisian', 'ga-IE': 'Irish', 'gl': 'Galician', 'gn': 'Guarani', 'gom': 'Goan Konkani', 'ha': 'Hausa', 'he': 'Hebrew', 'hi': 'Hindi', 'hil': 'Hiligaynon', 'hr': 'Croatian', 'hsb': 'Sorbian, Upper', 'ht': 'Haitian', 'hu': 'Hungarian', 'hy-AM': 'Armenian', 'hyw': 'Armenian Western', 'ia': 'Interlingua', 'id': 'Indonesian', 'ie': 'Interlingue', 'ig': 'Igbo', 'is': 'Icelandic', 'it': 'Italian', 'izh': 'Izhorian', 'ja': 'Japanese', 'jbo': 'Lojban', 'ka': 'Georgian', 'kaa': 'Karakalpak', 'kab': 'Kabyle', 'kbd': 'Kabardian', 'ki': 'Kikuyu', 'kk': 'Kazakh', 'km': 'Khmer', 'kmr': 'Kurmanji Kurdish', 'kn': 'Kannada', 'knn': 'Konkani (Devanagari)', 'ko': 'Korean', 'kpv': 'Komi-Zyrian', 'kw': 'Cornish', 'ky': 'Kyrgyz', 'lb': 'Luxembourgish', 'lg': 'Luganda', 'lij': 'Ligurian', 'ln': 'Lingala', 'lo': 'Lao', 'lt': 'Lithuanian', 'lv': 'Latvian', 'mai': 'Maithili', 'mdf': 'Moksha', 'mg': 'Malagasy', 'mhr': 'Meadow Mari', 'mk': 'Macedonian', 'ml': 'Malayalam', 'mn': 'Mongolian', 'mni': 'Meetei Lon', 'mos': 'Mossi', 'mr': 'Marathi', 'mrj': 'Hill Mari', 'ms': 'Malay', 'mt': 'Maltese', 'my': 'Burmese', 'myv': 'Erzya', 'nan-tw': 'Taiwanese (Minnan)', 'nb-NO': 'Norwegian Bokmål', 'nd': 'IsiNdebele (North)', 'ne-NP': 'Nepali', 'nia': 'Nias', 'nl': 'Dutch', 'nn-NO': 'Norwegian Nynorsk', 'nr': 'IsiNdebele (South)', 'nso': 'Northern Sotho', 'nyn': 'Runyankole', 'oc': 'Occitan', 'om': 'Afaan Ormoo', 'or': 'Odia', 'pa-IN': 'Punjabi', 'pap-AW': 'Papiamento (Aruba)', 'pl': 'Polish', 'ps': 'Pashto', 'pt': 'Portuguese', 'quc': "K'iche'", 'quy': 'Quechua Chanka', 'rm-sursilv': 'Romansh Sursilvan', 'rm-vallader': 'Romansh Vallader', 'ro': 'Romanian', 'ru': 'Russian', 'rw': 'Kinyarwanda', 'sah': 'Sakha', 'sat': 'Santali (Ol Chiki)', 'sc': 'Sardinian', 'scn': 'Sicilian', 'sdh': 'Southern Kurdish', 'shi': 'Shilha', 'si': 'Sinhala', 'sk': 'Slovak', 'skr': 'Saraiki', 'sl': 'Slovenian', 'snk': 'Soninke', 'so': 'Somali', 'sq': 'Albanian', 'sr': 'Serbian', 'ss': 'Siswati', 'st': 'Southern Sotho', 'sv-SE': 'Swedish', 'sw': 'Swahili', 'syr': 'Syriac', 'ta': 'Tamil', 'te': 'Telugu', 'tg': 'Tajik', 'th': 'Thai', 'ti': 'Tigrinya', 'tig': 'Tigre', 'tk': 'Turkmen', 'tl': 'Tagalog', 'tn': 'Setswana', 'tok': 'Toki Pona', 'tr': 'Turkish', 'ts': 'Xitsonga', 'tt': 'Tatar', 'tw': 'Twi', 'ty': 'Tahitian', 'uby': 'Ubykh', 'udm': 'Udmurt', 'ug': 'Uyghur', 'uk': 'Ukrainian', 'ur': 'Urdu', 'uz': 'Uzbek', 've': 'Tshivenda', 'vec': 'Venetian', 'vi': 'Vietnamese', 'vot': 'Votic', 'xh': 'Xhosa', 'yi': 'Yiddish', 'yo': 'Yoruba', 'yue': 'Cantonese', 'zgh': 'Tamazight', 'zh-CN': 'Chinese (China)', 'zh-HK': 'Chinese (Hong Kong)', 'zh-TW': 'Chinese (Taiwan)', 'zu': 'Zulu'}

data/common_voice_11_0/n_shards.json

@@ -0,0 +1,702 @@
+{
+    "ab": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "ar": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "as": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "ast": {
+        "train": 1,
+        "dev": 0,
+        "test": 1,
+        "other": 1,
+        "invalidated": 0
+    },
+    "az": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "ba": {
+        "train": 3,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "bas": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "be": {
+        "train": 9,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "bg": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "bn": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 6,
+        "invalidated": 1
+    },
+    "br": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "ca": {
+        "train": 23,
+        "dev": 1,
+        "test": 1,
+        "other": 13,
+        "invalidated": 2
+    },
+    "ckb": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "cnh": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "cs": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "cv": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "cy": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "da": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "de": {
+        "train": 12,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 2
+    },
+    "dv": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "el": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "en": {
+        "train": 24,
+        "dev": 1,
+        "test": 1,
+        "other": 8,
+        "invalidated": 7
+    },
+    "eo": {
+        "train": 4,
+        "dev": 1,
+        "test": 1,
+        "other": 4,
+        "invalidated": 4
+    },
+    "es": {
+        "train": 6,
+        "dev": 1,
+        "test": 1,
+        "other": 30,
+        "invalidated": 2
+    },
+    "et": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "eu": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "fa": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "fi": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "fr": {
+        "train": 13,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 2
+    },
+    "fy-NL": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 2,
+        "invalidated": 1
+    },
+    "ga-IE": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "gl": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "gn": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "ha": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "hi": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "hsb": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 0,
+        "invalidated": 1
+    },
+    "hu": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "hy-AM": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "ia": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "id": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "ig": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "it": {
+        "train": 4,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "ja": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "ka": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "kab": {
+        "train": 4,
+        "dev": 1,
+        "test": 1,
+        "other": 3,
+        "invalidated": 1
+    },
+    "kk": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 0,
+        "invalidated": 1
+    },
+    "kmr": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "ky": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "lg": {
+        "train": 2,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "lt": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "lv": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "mdf": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "mhr": {
+        "train": 2,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "mk": {
+        "train": 1,
+        "dev": 0,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "ml": {
+        "train": 1,
+        "dev": 0,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "mn": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "mr": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "mrj": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "mt": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "myv": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "nan-tw": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "ne-NP": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "nl": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "nn-NO": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 0,
+        "invalidated": 1
+    },
+    "or": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
+        "other": 1,
+        "invalidated": 1
+    },
+    "pa-IN": {
+        "train": 1,
+        "dev": 1,
+        "test": 1,
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+    "sk": {
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+    "skr": {
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+    "zh-HK": {
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+    }
+}

data/common_voice_11_0/readme.txt

@@ -0,0 +1,47 @@
+
+see huggingface_echodict\NeMo\readme.txt
+    些数据集是这个项目需要用的
+
+
+需要 clone 这个 git-lfs 项目 https://ai.gitee.com/hf-datasets/common_voice_11_0，
+但要排除 audio 文件夹 clone 
+
+
+# 1. 设置环境变量，在 clone 时跳过自动下载 LFS 实体文件
+$env:GIT_LFS_SKIP_SMUDGE=1
+
+# 2. 克隆项目（此时只会下载代码和 LFS 文件的“指针”，速度会很快）
+git clone https://ai.gitee.com/hf-datasets/common_voice_11_0
+
+# 3. 进入项目目录
+cd common_voice_11_0
+
+# 4. 配置 LFS 排除规则，告诉 LFS 不要拉取 audio 文件夹下的内容
+git config lfs.fetchexclude "audio/**"
+
+# 5. 拉取项目中除了 audio 文件夹之外的其他 LFS 文件（如果有的话）
+git lfs pull
+
+
+
+
+
+现在需要拉 common_voice_11_0/audio/ja 这个文件夹，怎么做
+
+如果你现在只需要单独拉取 `audio/ja` 这个文件夹中的大文件，可以通过在 `git lfs pull` 时指定 `--include` 参数，并用 `--exclude=""` 临时覆盖掉之前设置的排除规则。
+
+请在终端中进入你的项目目录，然后执行以下命令：
+
+```powershell
+# 1. 确保当前在项目目录下
+cd common_voice_11_0
+
+# 2. 仅拉取 audio/ja 目录下的 LFS 文件，并临时清空排除规则
+git lfs pull --include="audio/ja/**" --exclude=""
+```
+
+**命令原理解释：**
+* `--include="audio/ja/**"`：告诉 Git LFS 本次只下载 `audio/ja` 及其所有子目录下的真实大文件。
+* `--exclude=""`：因为我们在上一步中给这个仓库全局配置了忽略整个 `audio` 文件夹（`lfs.fetchexclude "audio/**"`），这里传入空的 exclude 参数可以**临时覆盖**那个配置，从而保证 `ja` 文件夹不会被错误拦截，顺利下载。
+
+执行完毕后，`audio/ja` 里的音频文件就会从 LFS 替换为实际的物理文件了，而 `audio` 目录下的其他语言文件夹依然保持为指针状态，不会占用你的磁盘空间。

data/common_voice_11_0/release_stats.py

@@ -0,0 +1 @@
+STATS = {'bundleURLTemplate': 'cv-corpus-11.0-2022-09-21/cv-corpus-11.0-2022-09-21-{locale}.tar.gz', 'date': '2022-09-21', 'name': 'Common Voice Corpus 11.0', 'multilingual': True, 'locales': {'en': {'duration': 11152496587, 'buckets': {'dev': 16354, 'invalidated': 252599, 'other': 290846, 'reported': 4366, 'test': 16354, 'train': 948736, 'validated': 1618225}, 'reportedSentences': 4294, 'clips': 2161670, 'splits': {'accent': {'': 1}, 'age': {'': 0.37, 'twenties': 0.24, 'sixties': 0.04, 'thirties': 0.13, 'teens': 0.06, 'seventies': 0.01, 'fourties': 0.1, 'fifties': 0.05, 'eighties': 0, 'nineties': 0}, 'gender': {'': 0.37, 'male': 0.45, 'female': 0.15, 'other': 0.02}}, 'users': 84673, 'size': 79751937788, 'checksum': '0efd86ca6b40641b55d1411b7d3b1f1ab8626de4b207504953706df201d198a5', 'avgDurationSecs': 5.159, 'validDurationSecs': 8348752.95, 'totalHrs': 3097.91, 'validHrs': 2319.09}, 'fa': {'buckets': {'dev': 10288, 'invalidated': 13793, 'other': 24401, 'reported': 2168, 'test': 10288, 'train': 26951, 'validated': 309996}, 'reportedSentences': 2159, 'duration': 1392397316, 'clips': 348190, 'splits': {'accent': {'': 1}, 'age': {'': 0.25, 'twenties': 0.31, 'thirties': 0.37, 'fifties': 0.02, 'fourties': 0.03, 'teens': 0.03, 'sixties': 0}, 'gender': {'': 0.22, 'male': 0.71, 'female': 0.07, 'other': 0}}, 'users': 4124, 'size': 10237548588, 'checksum': 'e40247da130302d1dd71e5f25742a0f2f61e8627e7b674c13294967a23f6cf47', 'avgDurationSecs': 3.999, 'validDurationSecs': 1239661.1, 'totalHrs': 386.77, 'validHrs': 344.35}, 'fr': {'buckets': {'dev': 16089, 'invalidated': 57607, 'other': 14359, 'reported': 6586, 'test': 16089, 'train': 485034, 'validated': 652051}, 'reportedSentences': 6510, 'duration': 3623103766, 'clips': 724017, 'splits': {'accent': {'': 1}, 'age': {'twenties': 0.17, 'thirties': 0.16, '': 0.36, 'teens': 0.03, 'fourties': 0.14, 'fifties': 0.1, 'sixties': 0.03, 'seventies': 0.01, 'eighties': 0, 'nineties': 0}, 'gender': {'male': 0.61, '': 0.28, 'female': 0.1, 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data/common_voice_11_0/transcript/ja/train.tsv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:34b534ad4c3c0e76ad416095cefed0d8cc73c4a0273c1e16331a0f2f2cdee416
+size 1729826

how_to_use_cv11.py

@@ -0,0 +1,30 @@
+# Load the dataset (locally)
+
+from datasets import load_dataset
+
+cv_11 = load_dataset("mozilla-foundation/common_voice_11_0", "hi", split="train")
+
+# Stream the dataset
+
+from datasets import load_dataset
+
+cv_11 = load_dataset("mozilla-foundation/common_voice_11_0", "hi", split="train", streaming=True)
+
+print(next(iter(cv_11)))
+
+# Create a PyTorch dataloader
+
+from datasets import load_dataset
+from torch.utils.data.sampler import BatchSampler, RandomSampler
+
+cv_11 = load_dataset("mozilla-foundation/common_voice_11_0", "hi", split="train")
+batch_sampler = BatchSampler(RandomSampler(cv_11), batch_size=32, drop_last=False)
+dataloader = DataLoader(cv_11, batch_sampler=batch_sampler)
+
+# Create a streaming PyTorch dataloader
+
+from datasets import load_dataset
+from torch.utils.data import DataLoader
+
+cv_11 = load_dataset("mozilla-foundation/common_voice_11_0", "hi", split="train")
+dataloader = DataLoader(cv_11, batch_size=32)

readme.txt

@@ -36,5 +36,9 @@ conda run -n NeMo pip install datasets hydra-core omegaconf librosa soundfile
 
  git clone https://ai.gitee.com/hf-datasets/common_voice_11_0
 
-tar xzvf "/mnt/y/ai/Common Voice Scripted Speech 25.0 - Japanese.tar.gz" -C /mnt/e/huggingface_echodict/NeMo/data
-    wsl 解压数据
+    # tar xzvf "/mnt/y/ai/Common Voice Scripted Speech 25.0 - Japanese.tar.gz" -C /mnt/e/huggingface_echodict/NeMo/data
+        wsl 解压数据
+
+
+python .\convert_ja.py
+    转换 common_voice_11_0 中的 ja 数据