African-African Parallel Sentences
Collection
Collection of sentence pairs or parallel corpus across African Languages for machine translation.
•
703 items
•
Updated
Dataset Viewer
score
float32 1.04
1.25
⌀ | Fulah
stringlengths 10
400
⌀ | Ganda
stringlengths 10
500
|
|---|---|---|
1.248223
|
be contrary to, be diffident, be doubtful, be dubious,
|
eulogise okutenda, okusuuta,
|
1.213917
|
hakkunde leɗɗe diw-diwni,
|
Balituula (mu bittuluze) by'emiti gya Sidiri atemeddwako amaggwa.
|
1.208792
|
Gaɗuɓe ko wooɗi ɓe ummoto ɓe keɓa yonki ki re'ataa, nden gaɗuɓe ko halli boo ɓe ummoto ɓe taƴanee kiita.
|
29 ne bavaamu; abo abaakolanga ebirungi balizuukirira obulamu; n'abo abaakolanga ebitasaana balizuukirira omusango.
|
1.208253
|
Yimɓe ngari haa maako diga kootoy fuu.
|
Kyokka abantu ne beeyongera okujja gy'ali okuva ku njuyi zonna.+
|
1.207093
|
10 Laamu maaɗa wara, ko ngiɗɗaa waɗee nder duuniyaaru, no ɗum waɗirtee e dow.
|
10Obukama bwawe bwije, eby'ogonza bikorwe omu nsi nk'omwiguru.
|
1.200993
|
goɗɗo feere na?
|
Waliwo ekilala?
|
1.200762
|
36Onsay Yahuudiyankeeɓe ɓen wi'i: "Ndaaree no ɓe yiɗirnoo mo!"
|
3611:36 nny 3Awo Abayudaaya ne bagamba nti, "Ng'abadde amwagala nnyo!"
|
1.200736
|
4 To o wurtinii fuu baali maako, o ardotoɗi, ɗi tokkaymo, ngam e ɗi andi hononde maako.
|
4 Bw'amala okufulumya ezize zonna, azikulembera, n'endiga zimugoberera: kubanga zimumanyi eddoboozi.
|
1.197461
|
be contrary to, be diffident, be doubtful, be dubious,
|
ne liman ne okyanusta,
|
1.196953
|
wanna be kissing me?
|
ye bby wanna kiss em?
|
1.195458
|
Ɓe ngalaa ɓikkoy.
|
tebalina baana.
|
1.191255
|
30 Ngam daliila maajum ɗuuɗɓe nder mooɗon nyawi, tampi, ɗuuɗɓe boo maayi.
|
30 Mu mmwe kyemuvudde mubeeramu abangi abanafu n'abalwadde, era bangiko abeebaka:
|
1.189048
|
26 E nden ɗon nyalnde on toroto nder inde am.
|
26 Ku lunaku olwo mulimusaba mu liina lyange.
|
1.188703
|
be contrary to, be diffident, be doubtful, be dubious,
|
tatoe gyakufuu, kyoufuu,
|
1.188206
|
be contrary to, be diffident, be doubtful, be dubious,
|
Tatoe gyakufuu, kyoufuu,
|
1.188186
|
be contrary to, be diffident, be doubtful, be dubious,
|
n'okumuyita mu bulumi n'okubonaabona oba okugamba Yā 'Alī,
|
1.187915
|
9 Yimɓe fuu ngi'i o ɗon yaha, o ɗon yetta Allah.
|
9Abantu boona bamureeba naagyenda kandi naahimbisa Ruhanga.
|
1.186045
|
Ɓe luuri hakkunde maɓɓe.
|
Daga hk kuwa sukayi wa juna bye bye suka wuce.
|
1.185439
|
be contrary to, be diffident, be doubtful, be dubious,
|
ekikompe eky'obuyinike era eky'okunakuwala,
|
1.181997
|
11 Ɓurɗo teddude hakkunde mooɗon laatoo golloowo mooɗon.
|
11 Naye mu mmwe abasinga obukulu anaabanga muweereza wammwe.
|
1.180648
|
9 Ɓe paamaayi ko woni hakke, ngam ɓe koolaakiyam.
|
9 olw'ekibi, kubanga tebanzikiriza nze;
|
1.179548
|
Yangada ji hiitee burdii duudugo ha baabal be tinndiinii.
|
Kàli bwo bûli kulusha okuzimu, omanyâge bici obwo?
|
1.177841
|
mo anndaa huunde waawaa jakkoyaade,
|
N'omubi asobola okuba ow'amannyi bw'aba alina ekitone.
|
1.177597
|
2 Maɓɓitane min ɓerɗe mon.
|
2Mutukingulire emitima yanyu.
|
1.177511
|
be contrary to, be diffident, be doubtful, be dubious,
|
Ekyanya kitseme, Kuthya n'ekihugho,
|
1.17694
|
Hakkunde leydi e asamaan, ko e dow ɗuum Alla lonngini mo, yo o feewnu laana, kaawise.
|
Okugattibwa kw'ensi n'eggulu kwamubikkulirwa mu ngeri eyo, oyo eyali ku ntikko y'amadaala n'amutegeeza ebigambo eby'okugumya n'essuubi.
|
1.175428
|
be contrary to, be diffident, be doubtful, be dubious,
|
Akasondekanaya ekyambu n'erikihira okwa burobo n'eribughusa omwa maghetse.
|
1.173646
|
haaaa good to be back!
|
Ndi musanyufu nnyo okuba nti nnakomawo gy'ali!"
|
1.173606
|
8 "Ɓe barkiɗinaaɓe ɓe ɓerɗe laɓɗe, ngam ɓe ngi'ay Allah.
|
8 Balina omukisa abalina omutima omulongoofu: kubanga abo baliraba Katonda.
|
1.173237
|
wanna be kissing me?
|
Wud yooze kiss em?
|
1.172897
|
Ngal haaletee ko Zimbabwe.
|
Y zimbabwe estas.
|
1.171759
|
24 Haa jooni on toraaki goɗɗum nder inde am.
|
24 Ni ye buli eno timusabangaku kintu kyonakyona mu liina lyange.
|
1.17174
|
be contrary to, be diffident, be doubtful, be dubious,
|
gaali wala rap standing,
|
1.17156
|
18 Mi ɗon yetta Allah ngam mi ɓuri on fuu wolwugo bee ɗemɗe ɗe anndaaka.
|
18 Nneebaza Katonda, mbasinga mwenna okwogera ennimi;
|
1.170206
|
29 Ammaa to on laatake yimɓe Almasiihu, nden kam on asŋgol Ibrahiima boo, on keɓan ko Allah wi'no Ibrahiima.
|
29Obu muraaba muli ba Kristo, muli baijukuru b'Abburahamu, bagwetwa nkooku endagaano erukugamba.
|
1.1701
|
waawaaaaw i love that
|
Nyinza Okukwagala Enyo
|
1.169638
|
ha ha ha bad things happen to bad people
|
4) Ebintu ebibi bituuka eri abantu abalungi, era ebintu ebikyasinze obubi bituuka ku bantu abakyasinze obulungi.
|
1.169093
|
Allah woodi innde na?
|
Katonda Alina Erinnya? | Vidiyo
|
1.169024
|
29 Dow waɗooɓe annabaaku, ɗiɗo ɗum bo tato etta haala, horiiɓe wiɗitoo haala maɓɓe.
|
29 Ne bannabbi boogerenga babiri oba basatu, n'abalala baawulenga.
|
1.168599
|
Ngam min woni Jawmiraawo, kurgoowo on."
|
Ni nze asinga okubba engulu nakimo, ni nze okabaka."
|
1.168348
|
lol He has DEATH! (dum dum dum dum!)
|
Abafu baazinyemu ne basanyuka nnyo
|
1.168247
|
44 No waɗata koolooɗonyam to on ɗaɓɓita mantindirki, ammaa on ndurwaayi keɓon manteeki daga to Allah?
|
44 Mmwe muyinza mutya okukkiriza bwe mwagala okuweebwa ekitiibwa mwekka na mwekka ne mutanoonya kitiibwa ekiva eri Katonda ali omu yekka?
|
1.168028
|
Mi ɓurantaa ma ɓiɓɓe worɓe sappo na?"
|
Nze sikusingira abaana ekkumi?"
|
1.166215
|
be contrary to, be diffident, be doubtful, be dubious,
|
yeaaa,, mmg akak di era itu,,
|
1.165115
|
"Jooɗa gere nyaamo am,
|
"Tuula wano ku mukono gwange ogwa ddyo,
|
1.163813
|
be contrary to, be diffident, be doubtful, be dubious,
|
disown okuboola, okuboolereza, okuzaalukuka,
|
1.163765
|
2 Ngam a hokkiimo laamu dow yimɓe fuu, ngam o hokka fuu ɓe kokkuɗaamo yonki ki re'ataa.
|
2 nga bwe wamuwa obuyinza ku balina omubiri bonna, era bonna be wamuwa, abawe obulamu obutaggwaawo.
|
1.163538
|
15 Ndaa ko deftere Allah wi'i: "To on nani sawtu Allah hande, taa cattine ko'e mooɗon bana kaakaaji mon tuurtanno Allah."
|
15Manya ekyahandiikirwe nikigira kiti: Eri izooba, ku muraahurire eiraka rye, mutagangaaza emitima yaanyu nk'obu mwangomera.
|
1.162304
|
4 To o wurtini ɗi fuu yaasi, o ardoto ɗi, baali boo tokkoto mo, ngam ɗi anndi sawtu maako.
|
4 Bw'amala okufulumya ezize zonna, azikulembera, n'endiga zimugoberera: kubanga zimumanyi eddoboozi.
|
1.161952
|
Ammana ɓe njanngini hoore maɓɓe e daliila.
|
Bulyala bayisha barhudwirhekwo omutula,
|
1.161708
|
lol He has DEATH! (dum dum dum dum!)
|
Era ye wuyo anabera omusamize okuda mu kifo kyoyo eyafa.
|
1.161693
|
Gotta say, we'all dun good!
|
Teweeraliikirira, tuli ku mutimbagano ffenna!
|
1.160591
|
Ngam min woni Jawmiraawo, kurgoowo on."
|
Oba okwatiddwa obuggya olw'okuba ndi muntu mulungi?'
|
1.159675
|
9 Gam Alla haɓɓanii mo alkawal wi'i: "Mi wittaan mawuuri hande nii, mi tawan Saratu rimii ɓiɗɗo gorko."
|
9 Kubanga ekigambo ky'okusuubiza kye kino nti, "Mu kiseera nga kino Saala alizaala omwana owoobulenzi."
|
1.158693
|
Noy ngeendam Yeesu fuɗɗiri?
|
Obulamu bwa Yesu bw'atandika butya?
|
1.15806
|
15 Ndaa ko deftere Allah wi'i: "To on nani sawtu Allah hande, taa cattine ko'e mooɗon bana kaakaaji mon tuurtanno Allah."
|
15Kwo rhwanabwizirwe, mpu: Ene-ene, mukayumva izu lyâge, murhahûsagya emirhima yinyu, nka ku lya byàbâga omu bugomi.
|
1.15648
|
wanna be kissing me?
|
Will you kiss me bye bye?
|
1.156024
|
be contrary to, be diffident, be doubtful, be dubious,
|
Kikola ng'akasengejja okukuma ensasi oba kiyite omutenzaggulu.
|
1.155619
|
he's gonna be sooo good!
|
it's gonna be sooo awesome!
|
1.155588
|
be contrary to, be diffident, be doubtful, be dubious,
|
Oba ani akola kasiru oba omuzibe w'amatu oba
|
1.155588
|
be contrary to, be diffident, be doubtful, be dubious,
|
Oba aba üba Oba'ammagau,
|
1.155205
|
Hol sifaa suka hannde e fuuta?
|
Mwana mulenzi ogamba otya leero?
|
1.155122
|
Gotta be soon, right?
|
nti yabadde anoonya bwangu, ekituufu nze
|
1.155023
|
24 Ɗu'um ɗum waɗu ko Yahaya suree nder suudu cural.
|
24 Ekyo kikabaho Yohaana atakatairwe mu kihome.
|
1.154037
|
A ɗon esta yimɓe ɓe nuɗɗina fewre.
|
era ababe ne bwe baba mu busibe, tabanyooma.
|
1.15344
|
Beijo grande e suuuuper obrigada!;)
|
ekikompe ekigazi era ekinene;
|
1.153244
|
29 Haaldooɓe annabaaku du, ɗiɗo naa tato tan kaala, de heddiiɓe ɓeen kiinya haala maɓɓe kaan.
|
29 Ne bannabbi boogerenga babiri oba basatu, n'abalala baawulenga.
|
1.153011
|
15 Ndaa ko deftere Allah wi'i: "To on nani sawtu Allah hande, taa cattine ko'e mooɗon bana kaakaaji mon tuurtanno Allah."
|
15 Kwo rhwanabwizirwe, mpu: Ene-ene, mukayumva izu lyâge, murhahûsagya emirhima yinyu, nka kulya byàbâga omu bugomi.
|
1.152702
|
25 Kadin e woodi fii ɗuɗɗum ɗum Yeesu waɗi.
|
25 Mbwenu aliho n'ebindi bingi ebyo Yesu yakozire.
|
1.152603
|
De ndaaree ko ngaɗuɗon!
|
Mulabe bwenkoze!
|
1.152111
|
15 Ndaa ko deftere Allah wi'i: "To on nani sawtu Allah hande, taa cattine ko'e mooɗon bana kaakaaji mon tuurtanno Allah."
|
15Kwo rhwanabwizirwe, mpu: Ene-ene, mukayumva izu lyâge, murhahûsagya emirhima yinyu, nka kulya byàbâga omu bugomi.
|
1.151981
|
11 Ɓurɗo teddude hakkunde mooɗon yo laato gollanoowo heddiiɓe ɓee.
|
11 Naye mu mmwe abasinga obukulu anaabanga muweereza wammwe.
|
1.151806
|
O wi'i: "Mawɗo, mi woodi habaru ngam maaɗa."
|
aye unena'mba: "Mu kitatyi kitabijibwe nakwivwene, kadi mu
|
1.150651
|
Ngam min woni Jawmiraawo, kurgoowo on."
|
"Ngame omukwati gwoohi na omunafaalama woo.
|
1.150492
|
3 O wi'i: "Mi ɗon wi'a on bee gooŋga: To on ngaylitaaki haa on laato bana ɓikkoy pamaroy, nden kam on nastataa laamu Allah sam.
|
3 N'abagamba nti, "Ddala ddala mbagamba nti bwe mutakyuke kufaanana ng'abaana abato temugenda kuyingira mu bwakabaka obw'omu ggulu.
|
1.15036
|
38 Ɗu'um waɗi ngam ɗum hebbina ko Annabi Icaaya wi'i, "Joomiraawo, moye jaɓi ko mbiiɗen?
|
Kubanga Isaaya ayogera nti Mukama, ani eyakkiriza ekigambo kyaffe? 17 Kale okukkiriza kuva mu kuwulira, n'okuwulira mu kigambo kya Kristo.
|
1.150018
|
To haala ka nanuɗon diga fuɗɗoode tabitake der ɓerɗe mooɗon, den kan, oon goodi kawtal e Ɓiɗɗo e Baaba.
|
Bwe munaakuumanga ekyo kye mwawulira okuva ku lubereberye, Omwana awamu ne Kitaffe banaabeeranga wamu nammwe.
|
1.149973
|
so beautiful.... wanna be there too^^
|
Awesome - wanna be there.
|
1.14959
|
be contrary to, be diffident, be doubtful, be dubious,
|
Ne bekyanga, ne beejubisa
|
1.149524
|
Muusa wi'i ɓe: "Nane le, onon tuurtooɓe!
|
Eki kikaleka ithwibuka ebya Biblia yikakanaya oku Musa bino: 'Mwayiyinia iniakalhangira Oyuthelholhawako.'
|
1.149278
|
Muusa wi'i ɓe: "Nane le, onon tuurtooɓe!
|
Moses omugambe, n'abo bona mubagambeVerse 1Lwaki onsibako akanyaanya, emikwano gyona ogenda o...
|
1.149121
|
hakkunde leɗɗe diw-diwni,
|
basadiya katti mund madyaak makkalyak,
|
1.148722
|
12 Ngam Ruuhu Ceniiɗo anndinan on ko mbi'oton wakkati maajum."
|
12 kubanga Omwoyo Omutukuvu anaabayigirizanga mu kiseera ekyo ebibagwanidde okwogera.
|
1.148483
|
be contrary to, be diffident, be doubtful, be dubious,
|
Bobi wine alabuddwa nga yakava e Luzira, wegendereze nyoo
|
1.148063
|
23 Koo moye ganyuɗoyam wanyii Nyaako am maa.
|
23Buli ankyawa aba akyawa ne Kitange.
|
1.148023
|
o nyawtii nyawuuji meeɗen."
|
"Yatuwonya endwadde zaffe,
|
1.147655
|
7 Kadi Allah waɗataa gooŋgaaku bee law haa suɓaaɓe muuɗum, wookananɓe mo jemma e naaŋge na? 8 Mi ɗon wi'a on, o waɗanan ɓe gooŋgaaku bee law.
|
7 Kale Katonda talisingawo nnyo kulamula abantu be, be yeerondera, abamukaabirira emisana n'ekiro ate ng'abagumiikiriza? 8 Mbagamba nti agenda kubalamula mangu.
|
1.147593
|
Ɓe naŋgi keni duniyaaru nayi fuu ngam taa ɗi mbifa haa lesdi malla haa ndiyam koo haa leɗɗe boo.
|
Oluvannyuma ne ndaba bamalayika bana nga bayimiridde ku nsonda nnya ez'ensi, nga bakutte empewo nnya ez'ensi, empewo yonna ereme okukunta ku nsi, newakubadde ku nnyanja, newakubadde ku muti gwonna.
|
1.147588
|
11 O ɗon mo " ina kooɗume fuu nder saa'iire mum.
|
11 Buli kimu yakikola nga kirungi mu kiseera kyakyo.
|
1.147351
|
Si tawii ko nanuɗon kon gila ka fuɗɗoode wonii ka ɓerɗe mon, haray onon kadi on humondirii e Ɓiɗɗo on e Baabaajo on.
|
Bwe munaakuumanga ekyo kye mwawulira okuva ku lubereberye, Omwana awamu ne Kitaffe banaabeeranga wamu nammwe.
|
1.147281
|
be contrary to, be diffident, be doubtful, be dubious,
|
amakomamawanga aga kaniki, n'ag'effulungu, n'ag'olumyufu,
|
1.147223
|
Oɗon laamii lesdi ndiin daga 1982.
|
Afuze eggwanga lino okuva mu 1982 okutuusa kati.
|
1.147112
|
30 "Mi waawataa waɗugo kooɗume bee hoore am.
|
30 Tewali kintu na kimu kye nnyinza kukola ku bwange.
|
1.147002
|
Ohoo, ngam daliilaaji tati:
|
Tusobola okukikkiriza lwa nsonga nga ssatu:
|
1.146583
|
En foti anndugo innde maako e jaati maako goɗɗi.
|
Ohatu dulu okulihonga edina laye nosho yo omaukwatya aye amwe.
|
1.146045
|
wadui 18% kuugal fere
|
18% bakola mulimu ekilala
|
1.145985
|
8 Naa kanko woni jayngol ngool, ammaa o warii gam saaydingo ngol e yimɓe.
|
8 Si ye yali ekitangaala ekyo,+ naye yajja okuwa obujulirwa ku kitangaala ekyo.
|
1.145464
|
be contrary to, be diffident, be doubtful, be dubious,
|
Va mu bifo ebibi eby'okubuusabuusa olinnye mw'ebyo ebya waggulu eby'okukkiriza n'okukakasa.
|
1.145242
|
15 "Ndeente e annabo'en fewooɓe, waranɓe haa mooɗon ɓe ɗon nandi bee baali, ammaa nder maɓɓe ɓe caafaali kalluɗi.
|
15 Mwekuume bannabbi ab'obulimba, abajjira mu byambalo by'endiga gye muli, naye munda gy'emisege egisikula.
|
1.145096
|
15 Ndaa ko deftere Allah wi'i: "To on nani sawtu Allah hande, taa cattine ko'e mooɗon bana kaakaaji mon tuurtanno Allah."
|
15 Kwo rhwanabwizirwe, mpu: Ene-ene, mukayumva izu lyâge, murhahûsagya emirhima yinyu, nka ku lya byàbâga omu bugomi.
|
End of preview. Expand
in Data Studio
Fulah-Ganda_Sentence-Pairs Dataset
This dataset contains sentence pairs for African languages along with similarity scores. It can be used for machine translation, sentence alignment, or other natural language processing tasks.
This dataset is based on the NLLBv1 dataset, published on OPUS under an open-source initiative led by META. You can find more information here: OPUS - NLLB-v1
Metadata
- File Name: Fulah-Ganda_Sentence-Pairs
- Number of Rows: 91895
- Number of Columns: 3
- Columns: score, Fulah, Ganda
Dataset Description
The dataset contains sentence pairs in African languages with an associated similarity score. Each row consists of three columns:
score: The similarity score between the two sentences (range from 0 to 1).Fulah: The first sentence in the pair (language 1).Ganda: The second sentence in the pair (language 2).
This dataset is intended for use in training and evaluating machine learning models for tasks like translation, sentence similarity, and cross-lingual transfer learning.
References
Below are papers related to how the data was collected and used in various multilingual and cross-lingual applications:
[1] Holger Schwenk and Matthijs Douze, Learning Joint Multilingual Sentence Representations with Neural Machine Translation, ACL workshop on Representation Learning for NLP, 2017
[2] Holger Schwenk and Xian Li, A Corpus for Multilingual Document Classification in Eight Languages, LREC, pages 3548-3551, 2018.
[3] Holger Schwenk, Filtering and Mining Parallel Data in a Joint Multilingual Space ACL, July 2018
[4] Alexis Conneau, Guillaume Lample, Ruty Rinott, Adina Williams, Samuel R. Bowman, Holger Schwenk and Veselin Stoyanov, XNLI: Cross-lingual Sentence Understanding through Inference, EMNLP, 2018.
[5] Mikel Artetxe and Holger Schwenk, Margin-based Parallel Corpus Mining with Multilingual Sentence Embeddings arXiv, Nov 3 2018.
[6] Mikel Artetxe and Holger Schwenk, Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond arXiv, Dec 26 2018.
[7] Holger Schwenk, Vishrav Chaudhary, Shuo Sun, Hongyu Gong and Paco Guzman, WikiMatrix: Mining 135M Parallel Sentences in 1620 Language Pairs from Wikipedia arXiv, July 11 2019.
[8] Holger Schwenk, Guillaume Wenzek, Sergey Edunov, Edouard Grave and Armand Joulin CCMatrix: Mining Billions of High-Quality Parallel Sentences on the WEB
[9] Paul-Ambroise Duquenne, Hongyu Gong, Holger Schwenk, Multimodal and Multilingual Embeddings for Large-Scale Speech Mining, NeurIPS 2021, pages 15748-15761.
[10] Kevin Heffernan, Onur Celebi, and Holger Schwenk, Bitext Mining Using Distilled Sentence Representations for Low-Resource Languages
- Downloads last month
- 8
Size of downloaded dataset files:
14.3 MB
Size of the auto-converted Parquet files:
10.9 MB
Number of rows:
91,895