File size: 3,869 Bytes
312c785
 
ca68712
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
c3109e0
ca68712
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
312c785
ca68712
c3109e0
 
fd7154c
c3109e0
9c1b2c8
 
 
 
c3109e0
9c1b2c8
c3abc14
 
9c1b2c8
9478075
8ba83f6
c3abc14
 
 
 
 
 
 
 
fd7154c
c3abc14
 
 
ac0af25
 
 
 
 
 
 
 
 
 
 
 
 
 
2b9a070
 
fd7154c
 
 
 
 
 
 
 
 
 
 
 
 
2b9a070
 
4738475
dde617f
59e1dfb
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
---
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 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/HbzC1C-uHe25ewTy2wyoK.png" width=7% height=7%> 
This is an output of the European Project UTTER (Unified Transcription and Translation for Extended Reality) funded by European Union’s Horizon Europe Research and Innovation programme under grant agreement number 101070631.

For more information please visit https://he-utter.eu/