|
--- |
|
language: multilingual |
|
datasets: |
|
- common_voice |
|
- multilingual_librispeech |
|
- covost2 |
|
tags: |
|
- speech |
|
- xls_r |
|
- automatic-speech-recognition |
|
- xls_r_translation |
|
pipeline_tag: automatic-speech-recognition |
|
license: apache-2.0 |
|
widget: |
|
- example_title: Swedish |
|
src: https://cdn-media.huggingface.co/speech_samples/cv_swedish_1.mp3 |
|
- example_title: Arabic |
|
src: https://cdn-media.huggingface.co/speech_samples/common_voice_ar_19058308.mp3 |
|
- example_title: Russian |
|
src: https://cdn-media.huggingface.co/speech_samples/common_voice_ru_18849022.mp3 |
|
- example_title: German |
|
src: https://cdn-media.huggingface.co/speech_samples/common_voice_de_17284683.mp3 |
|
- example_title: French |
|
src: https://cdn-media.huggingface.co/speech_samples/common_voice_fr_17299386.mp3 |
|
- example_title: Indonesian |
|
src: https://cdn-media.huggingface.co/speech_samples/common_voice_id_19051309.mp3 |
|
- example_title: Italian |
|
src: https://cdn-media.huggingface.co/speech_samples/common_voice_it_17415776.mp3 |
|
- example_title: Japanese |
|
src: https://cdn-media.huggingface.co/speech_samples/common_voice_ja_19482488.mp3 |
|
- example_title: Mongolian |
|
src: https://cdn-media.huggingface.co/speech_samples/common_voice_mn_18565396.mp3 |
|
- example_title: Dutch |
|
src: https://cdn-media.huggingface.co/speech_samples/common_voice_nl_17691471.mp3 |
|
- example_title: Russian |
|
src: https://cdn-media.huggingface.co/speech_samples/common_voice_ru_18849022.mp3 |
|
- example_title: Turkish |
|
src: https://cdn-media.huggingface.co/speech_samples/common_voice_tr_17341280.mp3 |
|
- example_title: Catalan |
|
src: https://cdn-media.huggingface.co/speech_samples/common_voice_ca_17367522.mp3 |
|
- example_title: English |
|
src: https://cdn-media.huggingface.co/speech_samples/common_voice_en_18301577.mp3 |
|
- example_title: Dutch |
|
src: https://cdn-media.huggingface.co/speech_samples/common_voice_nl_17691471.mp3 |
|
--- |
|
|
|
# Wav2Vec2-XLS-R-2B-22-16 (XLS-R-Any-to-Any) |
|
|
|
Facebook's Wav2Vec2 XLS-R fine-tuned for **Speech Translation.** |
|
|
|
![model image](https://raw.githubusercontent.com/patrickvonplaten/scientific_images/master/xls_r.png) |
|
|
|
This is a [SpeechEncoderDecoderModel](https://huggingface.co/transformers/model_doc/speechencoderdecoder.html) model. |
|
The encoder was warm-started from the [**`facebook/wav2vec2-xls-r-2b`**](https://huggingface.co/facebook/wav2vec2-xls-r-2b) checkpoint and |
|
the decoder from the [**`facebook/mbart-large-50`**](https://huggingface.co/facebook/mbart-large-50) checkpoint. |
|
Consequently, the encoder-decoder model was fine-tuned on `{input_lang}` -> `{output_lang}` translation pairs |
|
of the [Covost2 dataset](https://huggingface.co/datasets/covost2). |
|
|
|
The model can translate from the following spoken languages `{input_lang}` to the following written languages `{output_lang}`: |
|
|
|
`{input_lang}` -> `{output_lang}` |
|
|
|
with `{input_lang}` one of: |
|
|
|
{`en`, `fr`, `de`, `es`, `ca`, `it`, `ru`, `zh-CN`, `pt`, `fa`, `et`, `mn`, `nl`, `tr`, `ar`, `sv-SE`, `lv`, `sl`, `ta`, `ja`, `id`, `cy`} |
|
|
|
and `{output_lang}`: |
|
|
|
{`en`, `de`, `tr`, `fa`, `sv-SE`, `mn`, `zh-CN`, `cy`, `ca`, `sl`, `et`, `id`, `ar`, `ta`, `lv`, `ja`} |
|
|
|
## Usage |
|
|
|
### Demo |
|
|
|
The model can be tested on [**this space**](https://huggingface.co/spaces/facebook/XLS-R-2B-22-16). |
|
You can select the target language, record some audio in any of the above mentioned input languages, |
|
and then sit back and see how well the checkpoint can translate the input. |
|
|
|
### Example |
|
|
|
As this a standard sequence to sequence transformer model, you can use the `generate` method to generate the |
|
transcripts by passing the speech features to the model. |
|
|
|
You can use the model directly via the ASR pipeline. By default, the checkpoint will |
|
translate spoken English to written German. To change the written target language, |
|
you need to pass the correct `forced_bos_token_id` to `generate(...)` to condition |
|
the decoder on the correct target language. |
|
|
|
To select the correct `forced_bos_token_id` given your choosen language id, please make use |
|
of the following mapping: |
|
|
|
```python |
|
MAPPING = { |
|
"en": 250004, |
|
"de": 250003, |
|
"tr": 250023, |
|
"fa": 250029, |
|
"sv": 250042, |
|
"mn": 250037, |
|
"zh": 250025, |
|
"cy": 250007, |
|
"ca": 250005, |
|
"sl": 250052, |
|
"et": 250006, |
|
"id": 250032, |
|
"ar": 250001, |
|
"ta": 250044, |
|
"lv": 250017, |
|
"ja": 250012, |
|
} |
|
``` |
|
|
|
As an example, if you would like to translate to Swedish, you can do the following: |
|
|
|
```python |
|
from datasets import load_dataset |
|
from transformers import pipeline |
|
|
|
# select correct `forced_bos_token_id` |
|
forced_bos_token_id = MAPPING["sv"] |
|
|
|
# replace following lines to load an audio file of your choice |
|
librispeech_en = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation") |
|
audio_file = librispeech_en[0]["file"] |
|
|
|
asr = pipeline("automatic-speech-recognition", model="facebook/wav2vec2-xls-r-2b-22-to-16", feature_extractor="facebook/wav2vec2-xls-r-2b-22-to-16") |
|
|
|
translation = asr(audio_file, forced_bos_token_id=forced_bos_token_id) |
|
``` |
|
|
|
or step-by-step as follows: |
|
|
|
```python |
|
import torch |
|
from transformers import Speech2Text2Processor, SpeechEncoderDecoder |
|
from datasets import load_dataset |
|
|
|
model = SpeechEncoderDecoder.from_pretrained("facebook/wav2vec2-xls-r-2b-22-to-16") |
|
processor = Speech2Text2Processor.from_pretrained("facebook/wav2vec2-xls-r-2b-22-to-16") |
|
|
|
ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation") |
|
|
|
# select correct `forced_bos_token_id` |
|
forced_bos_token_id = MAPPING["sv"] |
|
|
|
inputs = processor(ds[0]["audio"]["array"], sampling_rate=ds[0]["audio"]["array"]["sampling_rate"], return_tensors="pt") |
|
generated_ids = model.generate(input_ids=inputs["input_features"], attention_mask=inputs["attention_mask"], forced_bos_token_id=forced_bos_token) |
|
transcription = processor.batch_decode(generated_ids) |
|
``` |
|
|
|
## More XLS-R models for `{lang}` -> `en` Speech Translation |
|
|
|
- [Wav2Vec2-XLS-R-300M-EN-15](https://huggingface.co/facebook/wav2vec2-xls-r-300m-en-to-15) |
|
- [Wav2Vec2-XLS-R-1B-EN-15](https://huggingface.co/facebook/wav2vec2-xls-r-1b-en-to-15) |
|
- [Wav2Vec2-XLS-R-2B-EN-15](https://huggingface.co/facebook/wav2vec2-xls-r-2b-en-to-15) |
|
- [Wav2Vec2-XLS-R-2B-22-16](https://huggingface.co/facebook/wav2vec2-xls-r-2b-22-to-16) |
|
|