metadata

license: cc-by-nc-4.0
language:
  - ab
  - af
  - am
  - ar
  - as
  - az
  - ba
  - be
  - bn
  - bo
  - bs
  - br
  - bg
  - ca
  - cs
  - cv
  - cy
  - da
  - de
  - dv
  - el
  - en
  - eo
  - et
  - eu
  - ee
  - fo
  - fa
  - tl
  - fi
  - fr
  - fy
  - ga
  - gl
  - gv
  - gn
  - gu
  - ht
  - ha
  - he
  - hi
  - hr
  - hu
  - hy
  - ig
  - ia
  - id
  - is
  - it
  - jv
  - ja
  - kn
  - ka
  - kk
  - km
  - rw
  - ky
  - ku
  - ko
  - lo
  - la
  - lv
  - ln
  - lt
  - lb
  - lg
  - ml
  - mr
  - mk
  - mg
  - mt
  - mn
  - mi
  - ms
  - my
  - ne
  - nl
  - nn
  - 'no'
  - oc
  - or
  - pa
  - pl
  - pt
  - ps
  - ro
  - ru
  - sa
  - si
  - sl
  - sk
  - sn
  - sd
  - so
  - st
  - es
  - sq
  - sc
  - sr
  - su
  - sw
  - sv
  - ta
  - tt
  - te
  - tg
  - th
  - tn
  - tk
  - tr
  - tw
  - ug
  - uk
  - ur
  - uz
  - vi
  - xh
  - yi
  - yo
  - zh

mHuBERT-147 models

mHuBERT-147 are compact and competitive multilingual general-purpose 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).

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},
}

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 and AISHELL-3
BibleTTS
ClovaCall
CommonVoice v11
Google TTS data: Javanese, Khmer, Nepali, Sundanese, South African Languages, Bengali Languages
IISc-MILE: Tamil, Kannada
Japanese Versatile Speech
Kokoro
Kosp2e
Media Speech: Turkish Only
Multilingual LibriSpeech
Samrómur
THCHS-30 and THUYG-20
VoxLingua107
VoxPopuli

Funding

This is an output of the European Project UTTER (Unified Transcription and Translation for Extended Reality) under grant number 101070631. For more information go to https://he-utter.eu/