सन्दर्भ:
en_de
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/en_de')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- विशेषताएँ :
{
"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
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/en_tr')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- विशेषताएँ :
{
"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
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/en_fa')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- विशेषताएँ :
{
"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
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/en_sv-SE')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- विशेषताएँ :
{
"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_mn
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/en_mn')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- विशेषताएँ :
{
"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
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/en_zh-CN')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- विशेषताएँ :
{
"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
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/en_cy')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- विशेषताएँ :
{
"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
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/en_ca')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- विशेषताएँ :
{
"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
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/en_sl')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- विशेषताएँ :
{
"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
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/en_et')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- विशेषताएँ :
{
"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
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/en_id')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- विशेषताएँ :
{
"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
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/en_ar')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- विशेषताएँ :
{
"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
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/en_ta')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- विशेषताएँ :
{
"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
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/en_lv')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- विशेषताएँ :
{
"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
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/en_ja')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 15531 |
'train' | 289430 |
'validation' | 15531 |
- विशेषताएँ :
{
"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
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/fr_en')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 14760 |
'train' | 207374 |
'validation' | 14760 |
- विशेषताएँ :
{
"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"
}
}
दे_एन
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/de_en')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 13511 |
'train' | 127834 |
'validation' | 13511 |
- विशेषताएँ :
{
"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
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/es_en')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 13221 |
'train' | 79015 |
'validation' | 13221 |
- विशेषताएँ :
{
"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
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/ca_en')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 12730 |
'train' | 95854 |
'validation' | 12730 |
- विशेषताएँ :
{
"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"
}
}
यह_एन
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/it_en')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 8951 |
'train' | 31698 |
'validation' | 8940 |
- विशेषताएँ :
{
"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
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/ru_en')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 6300 |
'train' | 12112 |
'validation' | 6110 |
- विशेषताएँ :
{
"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
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/zh-CN_en')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 4898 |
'train' | 7085 |
'validation' | 4843 |
- विशेषताएँ :
{
"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
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/pt_en')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 4023 |
'train' | 9158 |
'validation' | 3318 |
- विशेषताएँ :
{
"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
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/fa_en')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 3445 |
'train' | 53949 |
'validation' | 3445 |
- विशेषताएँ :
{
"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"
}
}
आदि
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/et_en')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 1571 |
'train' | 1782 |
'validation' | 1576 |
- विशेषताएँ :
{
"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
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/mn_en')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 1759 |
'train' | 2067 |
'validation' | 1761 |
- विशेषताएँ :
{
"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
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/nl_en')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 1699 |
'train' | 7108 |
'validation' | 1699 |
- विशेषताएँ :
{
"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
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/tr_en')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 1629 |
'train' | 3966 |
'validation' | 1624 |
- विशेषताएँ :
{
"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
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/ar_en')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 1695 |
'train' | 2283 |
'validation' | 1758 |
- विशेषताएँ :
{
"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
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/sv-SE_en')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 1595 |
'train' | 2160 |
'validation' | 1349 |
- विशेषताएँ :
{
"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
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/lv_en')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 1629 |
'train' | 2337 |
'validation' | 1125 |
- विशेषताएँ :
{
"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
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/sl_en')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 360 |
'train' | 1843 |
'validation' | 509 |
- विशेषताएँ :
{
"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
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/ta_en')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 786 |
'train' | 1358 |
'validation' | 384 |
- विशेषताएँ :
{
"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
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/ja_en')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 684 |
'train' | 1119 |
'validation' | 635 |
- विशेषताएँ :
{
"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
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/id_en')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 844 |
'train' | 1243 |
'validation' | 792 |
- विशेषताएँ :
{
"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
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:covost2/cy_en')
- विवरण :
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"])
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
विभाजित करना | उदाहरण |
---|---|
'test' | 690 |
'train' | 1241 |
'validation' | 690 |
- विशेषताएँ :
{
"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"
}
}