Referencje:
en_de
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/en_de')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- Cechy :
{
"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
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/en_tr')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- Cechy :
{
"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
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/en_fa')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- Cechy :
{
"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_sv-SE
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/en_sv-SE')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- Cechy :
{
"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"
}
}
pl_mn
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/en_mn')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- Cechy :
{
"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
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/en_zh-CN')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- Cechy :
{
"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
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/en_cy')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- Cechy :
{
"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
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/en_ca')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- Cechy :
{
"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_sl
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/en_sl')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- Cechy :
{
"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
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/en_et')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- Cechy :
{
"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
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/en_id')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- Cechy :
{
"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
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/en_ar')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- Cechy :
{
"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
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/en_ta')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- Cechy :
{
"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
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/en_lv')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- Cechy :
{
"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
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/en_ja')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- Cechy :
{
"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
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/fr_en')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 14760 |
'train' | 207374 |
'validation' | 14760 |
- Cechy :
{
"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
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/de_en')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 13511 |
'train' | 127834 |
'validation' | 13511 |
- Cechy :
{
"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
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/es_en')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 13221 |
'train' | 79015 |
'validation' | 13221 |
- Cechy :
{
"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
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/ca_en')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 12730 |
'train' | 95854 |
'validation' | 12730 |
- Cechy :
{
"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"
}
}
to_en
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/it_en')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 8951 |
'train' | 31698 |
'validation' | 8940 |
- Cechy :
{
"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
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/ru_en')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 6300 |
'train' | 12112 |
'validation' | 6110 |
- Cechy :
{
"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
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/zh-CN_en')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 4898 |
'train' | 7085 |
'validation' | 4843 |
- Cechy :
{
"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
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/pt_en')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 4023 |
'train' | 9158 |
'validation' | 3318 |
- Cechy :
{
"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
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/fa_en')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 3445 |
'train' | 53949 |
'validation' | 3445 |
- Cechy :
{
"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
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/et_en')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 1571 |
'train' | 1782 |
'validation' | 1576 |
- Cechy :
{
"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
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/mn_en')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 1759 |
'train' | 2067 |
'validation' | 1761 |
- Cechy :
{
"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
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/nl_en')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 1699 |
'train' | 7108 |
'validation' | 1699 |
- Cechy :
{
"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
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/tr_en')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 1629 |
'train' | 3966 |
'validation' | 1624 |
- Cechy :
{
"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
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/ar_en')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 1695 |
'train' | 2283 |
'validation' | 1758 |
- Cechy :
{
"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
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/sv-SE_en')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 1595 |
'train' | 2160 |
'validation' | 1349 |
- Cechy :
{
"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
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/lv_en')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 1629 |
'train' | 2337 |
'validation' | 1125 |
- Cechy :
{
"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
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/sl_en')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 360 |
'train' | 1843 |
'validation' | 509 |
- Cechy :
{
"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
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/ta_en')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 786 |
'train' | 1358 |
'validation' | 384 |
- Cechy :
{
"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
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/ja_en')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 684 |
'train' | 1119 |
'validation' | 635 |
- Cechy :
{
"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
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/id_en')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 844 |
'train' | 1243 |
'validation' | 792 |
- Cechy :
{
"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
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:covost2/cy_en')
- Opis :
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"])
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 690 |
'train' | 1241 |
'validation' | 690 |
- Cechy :
{
"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"
}
}