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