مراجع:
ar_de
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/en_de')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- سمات :
{
"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_tr
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/en_tr')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- سمات :
{
"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_fa
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/en_fa')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- سمات :
{
"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_sv-SE
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/en_sv-SE')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- سمات :
{
"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_mn
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/en_mn')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- سمات :
{
"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_zh-CN
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/en_zh-CN')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/en_cy')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- سمات :
{
"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_ca
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/en_ca')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- سمات :
{
"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_sl
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/en_sl')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- سمات :
{
"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_et
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/en_et')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- سمات :
{
"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_id
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/en_id')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/en_ar')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- سمات :
{
"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_ta
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/en_ta')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- سمات :
{
"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_lv
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/en_lv')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- سمات :
{
"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_ja
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/en_ja')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/fr_en')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 14760 |
'train' | 207374 |
'validation' | 14760 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/de_en')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 13511 |
'train' | 127834 |
'validation' | 13511 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/es_en')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 13221 |
'train' | 79015 |
'validation' | 13221 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/ca_en')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 12730 |
'train' | 95854 |
'validation' | 12730 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/it_en')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 8951 |
'train' | 31698 |
'validation' | 8940 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/ru_en')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 6300 |
'train' | 12112 |
'validation' | 6110 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/zh-CN_en')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 4898 |
'train' | 7085 |
'validation' | 4843 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/pt_en')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 4023 |
'train' | 9158 |
'validation' | 3318 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/fa_en')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 3445 |
'train' | 53949 |
'validation' | 3445 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/et_en')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 1571 |
'train' | 1782 |
'validation' | 1576 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/mn_en')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 1759 |
'train' | 2067 |
'validation' | 1761 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/nl_en')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 1699 |
'train' | 7108 |
'validation' | 1699 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/tr_en')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 1629 |
'train' | 3966 |
'validation' | 1624 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/ar_en')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 1695 |
'train' | 2283 |
'validation' | 1758 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/sv-SE_en')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 1595 |
'train' | 2160 |
'validation' | 1349 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/lv_en')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 1629 |
'train' | 2337 |
'validation' | 1125 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/sl_en')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 360 |
'train' | 1843 |
'validation' | 509 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/ta_en')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 786 |
'train' | 1358 |
'validation' | 384 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/ja_en')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 684 |
'train' | 1119 |
'validation' | 635 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/id_en')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 844 |
'train' | 1243 |
'validation' | 792 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:covost2/cy_en')
- وصف :
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"])
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 690 |
'train' | 1241 |
'validation' | 690 |
- سمات :
{
"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"
}
}