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---
license: cc-by-nc-4.0
language:
- ab
- af
- am
- ar
- as
- az
- ba
- be
- bn
- bo
- bs
- br
- bg
- ca
- cs
- cv
- cy
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- eu
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- nl
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- ru
- sa
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- es
- sq
- sc
- sr
- su
- sw
- sv
- ta
- tt
- te
- tg
- th
- tn
- tk
- tr
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- ug
- uk
- ur
- uz
- vi
- xh
- yi
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---
## mHuBERT-147 models
mHuBERT-147 are compact and competitive multilingual HuBERT models trained on 90K hours of open-license data in 147 languages.
This repository contains:
* Fairseq checkpoint (original);
* HuggingFace checkpoint;
* Faiss index for continuous pre-training (OPQ16_64,IVF1000_HNSW32,PQ16x4fsr).
# Additional Information
**Manifest list:** https://huggingface.co/utter-project/mHuBERT-147-base-3rd-iter/tree/main/manifest
Please note that since training, there were CommonVoice removal requests. This means that some of the listed files are no longer available.
**Fairseq fork:** https://github.com/utter-project/fairseq
**Scripts for pre-processing/faiss clustering:** https://github.com/utter-project/mHuBERT-147-scripts
**Languages present not indexed by Huggingface:** Asturian (ast), Basaa (bas), Cebuano (ceb), Central Kurdish/Sorani (ckb), Hakha Chin (cnh), Hawaiian (haw), Upper Sorbian (hsb) Kabyle (kab), Moksha (mdf), Meadow Mari (mhr), Hill Mari (mrj), Erzya (myv), Taiwanese Hokkien (nan-tw), Sursilvan (rm-sursilv), Vallader (rm-vallader), Sakha (sah), Santali (sat), Scots (sco), Saraiki (skr), Tigre (tig), Tok Pisin (tpi), Akwapen Twi (tw-akuapem), Asante Twi (tw-asante), Votic (vot), Waray (war), Cantonese (yue).
# Datasets Included
For ASR/ST/TTS datasets, only train set is used.
* [Aishell](https://www.openslr.org/33/) and [AISHELL-3](https://www.openslr.org/93/)
* [BibleTTS](https://www.openslr.org/129/)
* [ClovaCall](https://github.com/clovaai/ClovaCall)
* [CommonVoice v11](https://commonvoice.mozilla.org/en/datasets)
* Google TTS data: [Javanese](https://www.openslr.org/41/), [Khmer](https://www.openslr.org/42/), [Nepali](https://www.openslr.org/43/), [Sundanese](https://www.openslr.org/44/), [South African Languages](https://www.openslr.org/32/), [Bengali Languages](https://www.openslr.org/37/)
* IISc-MILE: [Tamil](https://www.openslr.org/127/), [Kannada](https://www.openslr.org/126/)
* [Japanese Versatile Speech](https://sites.google.com/site/shinnosuketakamichi/research-topics/jvs_corpus)
* [Kokoro](https://github.com/kaiidams/Kokoro-Speech-Dataset)
* [Kosp2e](https://github.com/warnikchow/kosp2e)
* Media Speech: [Turkish Only](https://www.openslr.org/108/)
* [Multilingual LibriSpeech](https://www.openslr.org/94/)
* [Samrómur](https://www.openslr.org/128/)
* [THCHS-30](https://www.openslr.org/18/) and [THUYG-20](https://www.openslr.org/22/)
* [VoxLingua107](https://bark.phon.ioc.ee/voxlingua107/)
* [VoxPopuli](https://github.com/facebookresearch/voxpopuli/)
# Citing
```
@inproceedings{boito2024mhubert,
author={Marcely Zanon Boito, Vivek Iyer, Nikolaos Lagos, Laurent Besacier, Ioan Calapodescu},
title={{mHuBERT-147: A Compact Multilingual HuBERT Model}},
year=2024,
booktitle={Interspeech 2024},
}
```
# Funding
<img src="https://cdn-uploads.huggingface.co/production/uploads/62262e19d36494a6f743a28d/b9g2O68Kj7mAG3n_SLWEe.png" width=20% height=20%>
This is an output of the European Project UTTER (Unified Transcription and Translation for Extended Reality) under grant number 101070631.
For more information please visit https://he-utter.eu/
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