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Datasets:
Batuka0901
/
fluers-mn

Tasks:
Automatic Speech Recognition
Modalities:
Audio
Text
Formats:
parquet
Languages:
Mongolian
Size:
1K - 10K
Libraries:
Datasets
Dask
Polars
Dataset card Data Studio Files
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Batuka0901 commited on
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README.md CHANGED
@@ -3,6 +3,165 @@ language:
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  - mn
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  task_categories:
5
  - automatic-speech-recognition
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  # fleurs-mn
 
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  - mn
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  task_categories:
5
  - automatic-speech-recognition
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+ dataset_info:
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+ features:
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+ - name: id
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+ dtype: int32
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+ - name: num_samples
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+ dtype: int32
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+ - name: audio
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+ dtype:
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+ audio:
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+ sampling_rate: 16000
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+ - name: transcription
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+ dtype: string
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+ - name: raw_transcription
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+ dtype: string
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+ - name: gender
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+ dtype:
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+ class_label:
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+ names:
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+ '0': male
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+ '1': female
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+ '2': other
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+ - name: lang_id
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+ dtype:
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+ class_label:
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+ names:
31
+ '0': af_za
32
+ '1': am_et
33
+ '2': ar_eg
34
+ '3': as_in
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+ '4': ast_es
36
+ '5': az_az
37
+ '6': be_by
38
+ '7': bg_bg
39
+ '8': bn_in
40
+ '9': bs_ba
41
+ '10': ca_es
42
+ '11': ceb_ph
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+ '12': ckb_iq
44
+ '13': cmn_hans_cn
45
+ '14': cs_cz
46
+ '15': cy_gb
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+ '16': da_dk
48
+ '17': de_de
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+ '18': el_gr
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+ '19': en_us
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+ '20': es_419
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+ '21': et_ee
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+ '22': fa_ir
54
+ '23': ff_sn
55
+ '24': fi_fi
56
+ '25': fil_ph
57
+ '26': fr_fr
58
+ '27': ga_ie
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+ '28': gl_es
60
+ '29': gu_in
61
+ '30': ha_ng
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+ '31': he_il
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+ '32': hi_in
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+ '33': hr_hr
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+ '34': hu_hu
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+ '35': hy_am
67
+ '36': id_id
68
+ '37': ig_ng
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+ '38': is_is
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+ '39': it_it
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+ '40': ja_jp
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+ '41': jv_id
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+ '42': ka_ge
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+ '43': kam_ke
75
+ '44': kea_cv
76
+ '45': kk_kz
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+ '46': km_kh
78
+ '47': kn_in
79
+ '48': ko_kr
80
+ '49': ky_kg
81
+ '50': lb_lu
82
+ '51': lg_ug
83
+ '52': ln_cd
84
+ '53': lo_la
85
+ '54': lt_lt
86
+ '55': luo_ke
87
+ '56': lv_lv
88
+ '57': mi_nz
89
+ '58': mk_mk
90
+ '59': ml_in
91
+ '60': mn_mn
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+ '61': mr_in
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+ '62': ms_my
94
+ '63': mt_mt
95
+ '64': my_mm
96
+ '65': nb_no
97
+ '66': ne_np
98
+ '67': nl_nl
99
+ '68': nso_za
100
+ '69': ny_mw
101
+ '70': oc_fr
102
+ '71': om_et
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+ '72': or_in
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+ '73': pa_in
105
+ '74': pl_pl
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+ '75': ps_af
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+ '76': pt_br
108
+ '77': ro_ro
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+ '78': ru_ru
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+ '79': sd_in
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+ '80': sk_sk
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+ '81': sl_si
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+ '82': sn_zw
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+ '83': so_so
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+ '84': sr_rs
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+ '85': sv_se
117
+ '86': sw_ke
118
+ '87': ta_in
119
+ '88': te_in
120
+ '89': tg_tj
121
+ '90': th_th
122
+ '91': tr_tr
123
+ '92': uk_ua
124
+ '93': umb_ao
125
+ '94': ur_pk
126
+ '95': uz_uz
127
+ '96': vi_vn
128
+ '97': wo_sn
129
+ '98': xh_za
130
+ '99': yo_ng
131
+ '100': yue_hant_hk
132
+ '101': zu_za
133
+ '102': all
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+ - name: language
135
+ dtype: string
136
+ - name: lang_group_id
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+ dtype:
138
+ class_label:
139
+ names:
140
+ '0': western_european_we
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+ '1': eastern_european_ee
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+ '2': central_asia_middle_north_african_cmn
143
+ '3': sub_saharan_african_ssa
144
+ '4': south_asian_sa
145
+ '5': south_east_asian_sea
146
+ '6': chinese_japanase_korean_cjk
147
+ - name: duration
148
+ dtype: float64
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+ splits:
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+ - name: train
151
+ num_bytes: 1614786393.5682023
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+ num_examples: 3985
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+ - name: test
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+ num_bytes: 179510758.43179765
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+ num_examples: 443
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+ download_size: 1580284915
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+ dataset_size: 1794297152.0
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+ configs:
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+ - config_name: default
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+ data_files:
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+ - split: train
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+ path: data/train-*
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+ - split: test
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+ path: data/test-*
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  ---
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  # fleurs-mn