Robust speech recognition in 70+ LanguagesHi all,We are scaling multi-lingual speech recognition systems - come join us for the robust speech community event fromJan 24th to Feb 7th. With compute provided by OVHcould, we are going from 50 to 70+ languages, from 300M to 2B parameters models, and from toy evaluation datasets to real-world audio evaluation.What it is aboutThe goal of the event is to provide robust speech recognition systems in as many languages as possible to the community. We hope that especially low-resource languages will profit from this event.The main components of the speech recognition event consist of:Meta AI’s state-of-the-art XLS-R modelCommon Voice newest datasets 7 & 8Language model boosted decoding with Wav2Vec2Real-world audio for evaluationHow does it workParticipants have two weeks to build as manyrobustspeech recognition systems in as many languages as they want. In general, speech recognition systems can consist of:Fine-tuned speech recognition checkpoints (e.g.XLS-R)Language model boosted decoders (e.g.pyctcdecode + n-gram)Pre- and post-processing modules, such as noise-canceling, spelling correction, …During the event, you will have the opportunity to work on each of these components to build speech recognition systems in your favorite language!Each speech recognition system will automatically be evaluated on real-world audio (if available for the language). After the fine-tuning week, the best-performing systems of each language will receiveSWAG.What do I need to do to participateTo participate, simply fill outthis short google form. You will also need to create a Hugging Face Hub accounthereand join our discordhere-when joining the event’s discord channel please make sure to click on theemoji under the first message to access all relevant information.OVHcloudkindly offered to provide a limited about of GPUs for participants if needed - if you would like to have access to a GPU, please join the discord for more information*.Hereare a some in-detail videos on how to get started with setting up an OVHcloud account.This fine-tuning week should be especially interesting to native speakers of low-resource languages. Your language skills will help you select the best training data, and possibly build the best existing speech recognition system in your language.More in-detail information will be announced in the discord channel. We are looking forward to seeing you there!What do I getenjoy a bit of Hugging Face vibelearn how to build state-of-the-art speech recognition systemsfree compute to build a powerful fine-tuned model under your name on the Hubhugging face SWAG if you manage to have the best performing model in a language100 GPU hours fromOVHcloudif you manage to have the best performing model in a languageOpen-sourcely yours,Anton, Omar, Nico & Patrick
2022-01-12T17:50:56Z
Hey, is there any blog/resource available where I can learn how to build an Audio dataset for your own native language. So, that I can building speech recognition system during the event on the language that I want to work on.Also very excited for the event
2022-01-12T18:15:57Z
Hey@Modfiededition,That’s a great question!As a start, I think it always makes sense to see what datasets are already publicly available that you could use for your language. You could,e.g.see the Hugging Face Hub here and select thespeech-processingtag:Hugging Face – The AI community building the future.and then also your favorite language tag → then you can see which datasets are available through the Hub.Apart from this you can also check out this github page that lists a lot of publicly available speech datasets:GitHub - jim-schwoebel/voice_datasets: 🔊 A comprehensive list of open-source datasets for voice and sound computing (95+ datasets).If you want to extract audio/transcripts yourself, this is much more difficult and you also need to be careful about licensing. YouTube could be a good source, if the licenses allow it
2022-01-12T18:52:19Z
Great initiative! I am in!
2022-01-12T21:03:14Z
@patrickvonplatenInFine-Tune XLSR-Wav2Vec2 for low-resource ASR with 🤗 Transformersat correcting the “kenlm.arpa” file scriptFor me it was not working, the spacing to detect "0   < s > "line was incorrect
2022-01-12T21:20:29Z
RASMUS:itHey@RASMUS,Could you maybe open an issue on transformers or the blog with all the code to reproduce your error? More than happy to help you there then!
2022-01-12T21:55:10Z
Example script to edit kenlm arpa file does not work correctly in kaggle notebook · Issue #15128 · huggingface/transformers · GitHubOpened issue here@patrickvonplaten
2022-01-13T01:53:35Z
Thank you for the great initiative! I’d love to participate and push Mongolian open-source SST even further!Each speech recognition system will automatically be evaluated on real-world audio (if available for the language).Is there any list for languages those “will” be evaluated on real-world audio?Also is there any restriction for data source?
2022-01-13T05:34:58Z
@patrickvonplatensuper hyped to join! Question evaluation metrics. Some languages like Thai needs word tokenization. These tokenizations usually have many standards. Would it be better to use character-based metrics in this case (CER instead of WER). Example:airesearch/wav2vec2-large-xlsr-53-th · Hugging Face
2022-01-13T08:08:42Z
Great thanks!
2022-01-13T08:11:08Z
Hey@bayartsogt,That’s a great question! We are trying to get real-world audio for as many languages as possible. Currently we have real world audio forca.30 languages. We’ll try to find something good for Mongolian as wellIt would be great if you couldnotinclude the Common Voice “test” data split of your preferred language in the training data. Besides from that there is no restriction
2022-01-13T08:12:30Z
Hey@cstorm125,Very much agree! For certain tokenized languages we will evaluate on CER instead of WER. The CER metric is already available in datasets:Hugging Face – The AI community building the future.
2022-01-13T08:24:39Z
Please don’t forget to join discord under this link:Hugging Face
2022-01-13T08:46:08Z
Is this going to be individual event or is there option to team-up like in flax event?
2022-01-13T15:26:08Z
We’ll evaluate models individually and also hand out GPU compute for individuals. However, we do encourage participants to build teams on their own if they want to and think it helps improve their models
2022-01-14T17:29:14Z
My language(bashkir) is in the CommonVoice7. Can I use this data and train a model?
2022-01-16T06:51:14Z
Thank you so much@patrickvonplatenfor answering my questions.Hope we can finish strong!
2022-01-19T11:41:43Z
Great!I am quite interested in learning about state-of-the-art speech recognition systems.I am in!
2022-01-19T15:53:18Z
Hi! Great concept, really looking forward to learning a lot about robust speech systems!I have one question: In the post above you state that the event consists of using “Common Voice newest datasets 7 & 8” – Will Common Voice 8.0 be revealed/presented during this event? As far as I can tell, version 8 is not available on the CV website, and there are no allusions or references to it being upcoming from Mozilla or anywhere else in the event. The releases seem to have a 6 month interval, so I suppose it is about time for the next version
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