Referências:
en_de
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/en_de')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
en_tr
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/en_tr')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
en_fa
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/en_fa')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
pt_sv-SE
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/en_sv-SE')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
pt_mn
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/en_mn')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
pt_zh-CN
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/en_zh-CN')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
en_cy
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/en_cy')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
en_ca
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/en_ca')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
pt_sl
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/en_sl')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
en_et
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/en_et')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
en_id
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/en_id')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
en_ar
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/en_ar')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
en_ta
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/en_ta')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
en_lv
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/en_lv')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
pt_ja
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/en_ja')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
fr_en
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/fr_en')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 14760 |
'train' | 207374 |
'validation' | 14760 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
de_en
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/de_en')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 13511 |
'train' | 127834 |
'validation' | 13511 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
es_en
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/es_en')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 13221 |
'train' | 79015 |
'validation' | 13221 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
ca_en
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/ca_en')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 12730 |
'train' | 95854 |
'validation' | 12730 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
it_en
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/it_en')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 8951 |
'train' | 31698 |
'validation' | 8940 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
ru_en
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/ru_en')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 6300 |
'train' | 12112 |
'validation' | 6110 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
zh-CN_en
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/zh-CN_en')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 4898 |
'train' | 7085 |
'validation' | 4843 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
pt_en
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/pt_en')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 4023 |
'train' | 9158 |
'validation' | 3318 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
fa_en
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/fa_en')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 3445 |
'train' | 53949 |
'validation' | 3445 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
et_en
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/et_en')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 1571 |
'train' | 1782 |
'validation' | 1576 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
mn_en
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/mn_en')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 1759 |
'train' | 2067 |
'validation' | 1761 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
nl_en
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/nl_en')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 1699 |
'train' | 7108 |
'validation' | 1699 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
tr_en
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/tr_en')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 1629 |
'train' | 3966 |
'validation' | 1624 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
ar_en
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/ar_en')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 1695 |
'train' | 2283 |
'validation' | 1758 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
sv-SE_en
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/sv-SE_en')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 1595 |
'train' | 2160 |
'validation' | 1349 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
lv_en
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/lv_en')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 1629 |
'train' | 2337 |
'validation' | 1125 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
sl_en
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/sl_en')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 360 |
'train' | 1843 |
'validation' | 509 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
ta_en
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/ta_en')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 786 |
'train' | 1358 |
'validation' | 384 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
ja_en
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/ja_en')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 684 |
'train' | 1119 |
'validation' | 635 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
id_en
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/id_en')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 844 |
'train' | 1243 |
'validation' | 792 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
cy_en
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:covost2/cy_en')
- Descrição :
CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .mp3 format and is not converted to a float32 array. To convert, the audio
file to a float32 array, please make use of the `.map()` function as follows:
python
import torchaudio
def map_to_array(batch):
speech_array, _ = torchaudio.load(batch["file"])
batch["speech"] = speech_array.numpy()
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
Dividir | Exemplos |
---|---|
'test' | 690 |
'train' | 1241 |
'validation' | 690 |
- Características :
{
"client_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"translation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}