|
--- |
|
tags: |
|
- mms |
|
language: |
|
- ab |
|
- af |
|
- ak |
|
- am |
|
- ar |
|
- as |
|
- av |
|
- ay |
|
- az |
|
- ba |
|
- bm |
|
- be |
|
- bn |
|
- bi |
|
- bo |
|
- sh |
|
- br |
|
- bg |
|
- ca |
|
- cs |
|
- ce |
|
- cv |
|
- ku |
|
- cy |
|
- da |
|
- de |
|
- dv |
|
- dz |
|
- el |
|
- en |
|
- eo |
|
- et |
|
- eu |
|
- ee |
|
- fo |
|
- fa |
|
- fj |
|
- fi |
|
- fr |
|
- fy |
|
- ff |
|
- ga |
|
- gl |
|
- gn |
|
- gu |
|
- zh |
|
- ht |
|
- ha |
|
- he |
|
- hi |
|
- sh |
|
- hu |
|
- hy |
|
- ig |
|
- ia |
|
- ms |
|
- is |
|
- it |
|
- jv |
|
- ja |
|
- kn |
|
- ka |
|
- kk |
|
- kr |
|
- km |
|
- ki |
|
- rw |
|
- ky |
|
- ko |
|
- kv |
|
- lo |
|
- la |
|
- lv |
|
- ln |
|
- lt |
|
- lb |
|
- lg |
|
- mh |
|
- ml |
|
- mr |
|
- ms |
|
- mk |
|
- mg |
|
- mt |
|
- mn |
|
- mi |
|
- my |
|
- zh |
|
- nl |
|
- 'no' |
|
- 'no' |
|
- ne |
|
- ny |
|
- oc |
|
- om |
|
- or |
|
- os |
|
- pa |
|
- pl |
|
- pt |
|
- ms |
|
- ps |
|
- qu |
|
- qu |
|
- qu |
|
- qu |
|
- qu |
|
- qu |
|
- qu |
|
- qu |
|
- qu |
|
- qu |
|
- qu |
|
- qu |
|
- qu |
|
- qu |
|
- qu |
|
- qu |
|
- qu |
|
- qu |
|
- qu |
|
- qu |
|
- qu |
|
- qu |
|
- ro |
|
- rn |
|
- ru |
|
- sg |
|
- sk |
|
- sl |
|
- sm |
|
- sn |
|
- sd |
|
- so |
|
- es |
|
- sq |
|
- su |
|
- sv |
|
- sw |
|
- ta |
|
- tt |
|
- te |
|
- tg |
|
- tl |
|
- th |
|
- ti |
|
- ts |
|
- tr |
|
- uk |
|
- ms |
|
- vi |
|
- wo |
|
- xh |
|
- ms |
|
- yo |
|
- ms |
|
- zu |
|
- za |
|
license: cc-by-nc-4.0 |
|
datasets: |
|
- google/fleurs |
|
metrics: |
|
- acc |
|
--- |
|
|
|
# Massively Multilingual Speech (MMS) - Finetuned LID |
|
|
|
This checkpoint is a model fine-tuned for speech language identification (LID) and part of Facebook's [Massive Multilingual Speech project](https://research.facebook.com/publications/scaling-speech-technology-to-1000-languages/). |
|
This checkpoint is based on the [Wav2Vec2 architecture](https://huggingface.co/docs/transformers/model_doc/wav2vec2) and classifies raw audio input to a probability distribution over 512 output classes (each class representing a language). |
|
The checkpoint consists of **1 billion parameters** and has been fine-tuned from [facebook/mms-1b](https://huggingface.co/facebook/mms-1b) on 512 languages. |
|
|
|
## Table Of Content |
|
|
|
- [Example](#example) |
|
- [Supported Languages](#supported-languages) |
|
- [Model details](#model-details) |
|
- [Additional links](#additional-links) |
|
|
|
## Example |
|
|
|
This MMS checkpoint can be used with [Transformers](https://github.com/huggingface/transformers) to identify |
|
the spoken language of an audio. It can recognize the [following 512 languages](#supported-languages). |
|
|
|
Let's look at a simple example. |
|
|
|
First, we install transformers and some other libraries |
|
``` |
|
pip install torch accelerate torchaudio datasets |
|
pip install --upgrade transformers |
|
```` |
|
|
|
**Note**: In order to use MMS you need to have at least `transformers >= 4.30` installed. If the `4.30` version |
|
is not yet available [on PyPI](https://pypi.org/project/transformers/) make sure to install `transformers` from |
|
source: |
|
``` |
|
pip install git+https://github.com/huggingface/transformers.git |
|
``` |
|
|
|
Next, we load a couple of audio samples via `datasets`. Make sure that the audio data is sampled to 16000 kHz. |
|
|
|
```py |
|
from datasets import load_dataset, Audio |
|
|
|
# English |
|
stream_data = load_dataset("mozilla-foundation/common_voice_13_0", "en", split="test", streaming=True) |
|
stream_data = stream_data.cast_column("audio", Audio(sampling_rate=16000)) |
|
en_sample = next(iter(stream_data))["audio"]["array"] |
|
|
|
# Arabic |
|
stream_data = load_dataset("mozilla-foundation/common_voice_13_0", "ar", split="test", streaming=True) |
|
stream_data = stream_data.cast_column("audio", Audio(sampling_rate=16000)) |
|
ar_sample = next(iter(stream_data))["audio"]["array"] |
|
``` |
|
|
|
Next, we load the model and processor |
|
|
|
```py |
|
from transformers import Wav2Vec2ForSequenceClassification, AutoFeatureExtractor |
|
import torch |
|
|
|
model_id = "facebook/mms-lid-512" |
|
|
|
processor = AutoFeatureExtractor.from_pretrained(model_id) |
|
model = Wav2Vec2ForSequenceClassification.from_pretrained(model_id) |
|
``` |
|
|
|
Now we process the audio data, pass the processed audio data to the model to classify it into a language, just like we usually do for Wav2Vec2 audio classification models such as [ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition](https://huggingface.co/harshit345/xlsr-wav2vec-speech-emotion-recognition) |
|
|
|
```py |
|
# English |
|
inputs = processor(en_sample, sampling_rate=16_000, return_tensors="pt") |
|
|
|
with torch.no_grad(): |
|
outputs = model(**inputs).logits |
|
|
|
lang_id = torch.argmax(outputs, dim=-1)[0].item() |
|
detected_lang = model.config.id2label[lang_id] |
|
# 'eng' |
|
|
|
# Arabic |
|
inputs = processor(ar_sample, sampling_rate=16_000, return_tensors="pt") |
|
|
|
with torch.no_grad(): |
|
outputs = model(**inputs).logits |
|
|
|
lang_id = torch.argmax(outputs, dim=-1)[0].item() |
|
detected_lang = model.config.id2label[lang_id] |
|
# 'ara' |
|
``` |
|
|
|
To see all the supported languages of a checkpoint, you can print out the language ids as follows: |
|
```py |
|
processor.id2label.values() |
|
``` |
|
|
|
For more details, about the architecture please have a look at [the official docs](https://huggingface.co/docs/transformers/main/en/model_doc/mms). |
|
|
|
## Supported Languages |
|
|
|
This model supports 512 languages. Unclick the following to toogle all supported languages of this checkpoint in [ISO 639-3 code](https://en.wikipedia.org/wiki/ISO_639-3). |
|
You can find more details about the languages and their ISO 649-3 codes in the [MMS Language Coverage Overview](https://dl.fbaipublicfiles.com/mms/misc/language_coverage_mms.html). |
|
<details> |
|
<summary>Click to toggle</summary> |
|
|
|
- ara |
|
- cmn |
|
- eng |
|
- spa |
|
- fra |
|
- mlg |
|
- swe |
|
- por |
|
- vie |
|
- ful |
|
- sun |
|
- asm |
|
- ben |
|
- zlm |
|
- kor |
|
- ind |
|
- hin |
|
- tuk |
|
- urd |
|
- aze |
|
- slv |
|
- mon |
|
- hau |
|
- tel |
|
- swh |
|
- bod |
|
- rus |
|
- tur |
|
- heb |
|
- mar |
|
- som |
|
- tgl |
|
- tat |
|
- tha |
|
- cat |
|
- ron |
|
- mal |
|
- bel |
|
- pol |
|
- yor |
|
- nld |
|
- bul |
|
- hat |
|
- afr |
|
- isl |
|
- amh |
|
- tam |
|
- hun |
|
- hrv |
|
- lit |
|
- cym |
|
- fas |
|
- mkd |
|
- ell |
|
- bos |
|
- deu |
|
- sqi |
|
- jav |
|
- kmr |
|
- nob |
|
- uzb |
|
- snd |
|
- lat |
|
- nya |
|
- grn |
|
- mya |
|
- orm |
|
- lin |
|
- hye |
|
- yue |
|
- pan |
|
- jpn |
|
- kaz |
|
- npi |
|
- kik |
|
- kat |
|
- guj |
|
- kan |
|
- tgk |
|
- ukr |
|
- ces |
|
- lav |
|
- bak |
|
- khm |
|
- cak |
|
- fao |
|
- glg |
|
- ltz |
|
- xog |
|
- lao |
|
- mlt |
|
- sin |
|
- aka |
|
- sna |
|
- che |
|
- mam |
|
- ita |
|
- quc |
|
- srp |
|
- mri |
|
- tuv |
|
- nno |
|
- pus |
|
- eus |
|
- kbp |
|
- ory |
|
- lug |
|
- bre |
|
- luo |
|
- nhx |
|
- slk |
|
- ewe |
|
- fin |
|
- rif |
|
- dan |
|
- yid |
|
- yao |
|
- mos |
|
- quh |
|
- hne |
|
- xon |
|
- new |
|
- quy |
|
- est |
|
- dyu |
|
- ttq |
|
- bam |
|
- pse |
|
- uig |
|
- sck |
|
- ngl |
|
- tso |
|
- mup |
|
- dga |
|
- seh |
|
- lis |
|
- wal |
|
- ctg |
|
- bfz |
|
- bxk |
|
- ceb |
|
- kru |
|
- war |
|
- khg |
|
- bbc |
|
- thl |
|
- vmw |
|
- zne |
|
- sid |
|
- tpi |
|
- nym |
|
- bgq |
|
- bfy |
|
- hlb |
|
- teo |
|
- fon |
|
- kfx |
|
- bfa |
|
- mag |
|
- ayr |
|
- any |
|
- mnk |
|
- adx |
|
- ava |
|
- hyw |
|
- san |
|
- kek |
|
- chv |
|
- kri |
|
- btx |
|
- nhy |
|
- dnj |
|
- lon |
|
- men |
|
- ium |
|
- nga |
|
- nsu |
|
- prk |
|
- kir |
|
- bom |
|
- run |
|
- hwc |
|
- mnw |
|
- ubl |
|
- kin |
|
- rkt |
|
- xmm |
|
- iba |
|
- gux |
|
- ses |
|
- wsg |
|
- tir |
|
- gbm |
|
- mai |
|
- nyy |
|
- nan |
|
- nyn |
|
- gog |
|
- ngu |
|
- hoc |
|
- nyf |
|
- sus |
|
- bcc |
|
- hak |
|
- grt |
|
- suk |
|
- nij |
|
- kaa |
|
- bem |
|
- rmy |
|
- nus |
|
- ach |
|
- awa |
|
- dip |
|
- rim |
|
- nhe |
|
- pcm |
|
- kde |
|
- tem |
|
- quz |
|
- bba |
|
- kbr |
|
- taj |
|
- dik |
|
- dgo |
|
- bgc |
|
- xnr |
|
- kac |
|
- laj |
|
- dag |
|
- ktb |
|
- mgh |
|
- shn |
|
- oci |
|
- zyb |
|
- alz |
|
- wol |
|
- guw |
|
- nia |
|
- bci |
|
- sba |
|
- kab |
|
- nnb |
|
- ilo |
|
- mfe |
|
- xpe |
|
- bcl |
|
- haw |
|
- mad |
|
- ljp |
|
- gmv |
|
- nyo |
|
- kxm |
|
- nod |
|
- sag |
|
- sas |
|
- myx |
|
- sgw |
|
- mak |
|
- kfy |
|
- jam |
|
- lgg |
|
- nhi |
|
- mey |
|
- sgj |
|
- hay |
|
- pam |
|
- heh |
|
- nhw |
|
- yua |
|
- shi |
|
- mrw |
|
- hil |
|
- pag |
|
- cce |
|
- npl |
|
- ace |
|
- kam |
|
- min |
|
- pko |
|
- toi |
|
- ncj |
|
- umb |
|
- hno |
|
- ban |
|
- syl |
|
- bxg |
|
- nse |
|
- xho |
|
- mkw |
|
- nch |
|
- mas |
|
- bum |
|
- mww |
|
- epo |
|
- tzm |
|
- zul |
|
- lrc |
|
- ibo |
|
- abk |
|
- azz |
|
- guz |
|
- ksw |
|
- lus |
|
- ckb |
|
- mer |
|
- pov |
|
- rhg |
|
- knc |
|
- tum |
|
- nso |
|
- bho |
|
- ndc |
|
- ijc |
|
- qug |
|
- lub |
|
- srr |
|
- mni |
|
- zza |
|
- dje |
|
- tiv |
|
- gle |
|
- lua |
|
- swk |
|
- ada |
|
- lic |
|
- skr |
|
- mfa |
|
- bto |
|
- unr |
|
- hdy |
|
- kea |
|
- glk |
|
- ast |
|
- nup |
|
- sat |
|
- ktu |
|
- bhb |
|
- sgc |
|
- dks |
|
- ncl |
|
- emk |
|
- urh |
|
- tsc |
|
- idu |
|
- igb |
|
- its |
|
- kng |
|
- kmb |
|
- tsn |
|
- bin |
|
- gom |
|
- ven |
|
- sef |
|
- sco |
|
- trp |
|
- glv |
|
- haq |
|
- kha |
|
- rmn |
|
- sot |
|
- sou |
|
- gno |
|
- igl |
|
- efi |
|
- nde |
|
- rki |
|
- kjg |
|
- fan |
|
- wci |
|
- bjn |
|
- pmy |
|
- bqi |
|
- ina |
|
- hni |
|
- the |
|
- nuz |
|
- ajg |
|
- ymm |
|
- fmu |
|
- nyk |
|
- snk |
|
- esg |
|
- thq |
|
- pht |
|
- wes |
|
- pnb |
|
- phr |
|
- mui |
|
- tkt |
|
- bug |
|
- mrr |
|
- kas |
|
- zgb |
|
- lir |
|
- vah |
|
- ssw |
|
- iii |
|
- brx |
|
- rwr |
|
- kmc |
|
- dib |
|
- pcc |
|
- zyn |
|
- hea |
|
- hms |
|
- thr |
|
- wbr |
|
- bfb |
|
- wtm |
|
- blk |
|
- dhd |
|
- swv |
|
- zzj |
|
- niq |
|
- mtr |
|
- gju |
|
- kjp |
|
- haz |
|
- shy |
|
- nbl |
|
- aii |
|
- sjp |
|
- bns |
|
- brh |
|
- msi |
|
- tsg |
|
- tcy |
|
- kbl |
|
- noe |
|
- tyz |
|
- ahr |
|
- aar |
|
- wuu |
|
- kbd |
|
- bca |
|
- pwr |
|
- hsn |
|
- kua |
|
- tdd |
|
- bgp |
|
- abs |
|
- zlj |
|
- ebo |
|
- bra |
|
- nhp |
|
- tts |
|
- zyj |
|
- lmn |
|
- cqd |
|
- dcc |
|
- cjk |
|
- bfr |
|
- bew |
|
- arg |
|
- drs |
|
- chw |
|
- bej |
|
- bjj |
|
- ibb |
|
- tig |
|
- nut |
|
- jax |
|
- tdg |
|
- nlv |
|
- pch |
|
- fvr |
|
- mlq |
|
- kfr |
|
- nhn |
|
- tji |
|
- hoj |
|
- cpx |
|
- cdo |
|
- bgn |
|
- btm |
|
- trf |
|
- daq |
|
- max |
|
- nba |
|
- mut |
|
- hnd |
|
- ryu |
|
- abr |
|
- sop |
|
- odk |
|
- nap |
|
- gbr |
|
- czh |
|
- vls |
|
- gdx |
|
- yaf |
|
- sdh |
|
- anw |
|
- ttj |
|
- nhg |
|
- cgg |
|
- ifm |
|
- mdh |
|
- scn |
|
- lki |
|
- luz |
|
- stv |
|
- kmz |
|
- nds |
|
- mtq |
|
- knn |
|
- mnp |
|
- bar |
|
- mzn |
|
- gsw |
|
- fry |
|
|
|
</details> |
|
|
|
## Model details |
|
|
|
- **Developed by:** Vineel Pratap et al. |
|
- **Model type:** Multi-Lingual Automatic Speech Recognition model |
|
- **Language(s):** 512 languages, see [supported languages](#supported-languages) |
|
- **License:** CC-BY-NC 4.0 license |
|
- **Num parameters**: 1 billion |
|
- **Audio sampling rate**: 16,000 kHz |
|
- **Cite as:** |
|
|
|
@article{pratap2023mms, |
|
title={Scaling Speech Technology to 1,000+ Languages}, |
|
author={Vineel Pratap and Andros Tjandra and Bowen Shi and Paden Tomasello and Arun Babu and Sayani Kundu and Ali Elkahky and Zhaoheng Ni and Apoorv Vyas and Maryam Fazel-Zarandi and Alexei Baevski and Yossi Adi and Xiaohui Zhang and Wei-Ning Hsu and Alexis Conneau and Michael Auli}, |
|
journal={arXiv}, |
|
year={2023} |
|
} |
|
|
|
## Additional Links |
|
|
|
- [Blog post](https://ai.facebook.com/blog/multilingual-model-speech-recognition/) |
|
- [Transformers documentation](https://huggingface.co/docs/transformers/main/en/model_doc/mms). |
|
- [Paper](https://arxiv.org/abs/2305.13516) |
|
- [GitHub Repository](https://github.com/facebookresearch/fairseq/tree/main/examples/mms#asr) |
|
- [Other **MMS** checkpoints](https://huggingface.co/models?other=mms) |
|
- MMS base checkpoints: |
|
- [facebook/mms-1b](https://huggingface.co/facebook/mms-1b) |
|
- [facebook/mms-300m](https://huggingface.co/facebook/mms-300m) |
|
- [Official Space](https://huggingface.co/spaces/facebook/MMS) |
|
|
