fsicoli commited on
Commit
ab7de1e
1 Parent(s): 35d13ec

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +58 -0
README.md CHANGED
@@ -1,3 +1,61 @@
1
  ---
2
  license: mpl-2.0
 
 
3
  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
  ---
2
  license: mpl-2.0
3
+ language:
4
+ - pt
5
  ---
6
+ # Dataset Card for Common Voice Corpus 15.0
7
+
8
+ <!-- Provide a quick summary of the dataset. -->
9
+
10
+ This dataset is an unofficial converted version of the Mozilla Common Voice Corpus 15. It currently contains the following languages: Portuguese
11
+
12
+
13
+
14
+ ## How to use
15
+ 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.
16
+
17
+ For example, to download the Portuguese config, simply specify the corresponding language config name (i.e., "pt" for Portuguese):
18
+ ```
19
+ from datasets import load_dataset
20
+
21
+ cv_15 = load_dataset("fsicoli/common_voice_15_0", "pt", split="train")
22
+ ```
23
+ 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.
24
+
25
+ ```
26
+ from datasets import load_dataset
27
+
28
+ cv_15 = load_dataset("fsicoli/common_voice_15_0", "pt", split="train", streaming=True)
29
+
30
+ print(next(iter(cv_15)))
31
+ ```
32
+
33
+ Bonus: create a PyTorch dataloader directly with your own datasets (local/streamed).
34
+
35
+ ### Local
36
+ ```
37
+ from datasets import load_dataset
38
+ from torch.utils.data.sampler import BatchSampler, RandomSampler
39
+
40
+ cv_15 = load_dataset("fsicoli/common_voice_15_0", "pt", split="train")
41
+ batch_sampler = BatchSampler(RandomSampler(cv_15), batch_size=32, drop_last=False)
42
+ dataloader = DataLoader(cv_15, batch_sampler=batch_sampler)
43
+ ```
44
+
45
+ ### Streaming
46
+ ```
47
+ from datasets import load_dataset
48
+ from torch.utils.data import DataLoader
49
+
50
+ cv_15 = load_dataset("fsicoli/common_voice_15_0", "pt", split="train")
51
+ dataloader = DataLoader(cv_15, batch_size=32)
52
+ ```
53
+
54
+ To find out more about loading and preparing audio datasets, head over to hf.co/blog/audio-datasets.
55
+
56
+
57
+
58
+ ### Dataset Structure
59
+ Data Instances
60
+ 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.
61
+