African-African Parallel Sentences
Collection
Collection of sentence pairs or parallel corpus across African Languages for machine translation.
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703 items
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Updated
Dataset Viewer
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1.25
⌀ | Akan
stringlengths 10
496
⌀ | Twi
stringlengths 9
494
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1.249565
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20ɛte sɛ daeɛso, ɛberɛ a onipa anyaneɛ,
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20Ɛte sɛ adaeso, bere a onipa anyan,
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1.249331
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Obiara mma Agya no nkyԑn gye sԑ ᴐnam Me so.
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Obiara mma Agya no nkyɛn gye sɛ ɔnam me so. "
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1.249293
|
(1) Anwumabɔvolɛ ne zele bɛ kɛ: "Ɛnɛ kenle ye bɛwo bɛ Ngoanedievolɛ ne, mɔɔ le Awulae Kelaese ne wɔ Devidi sua zo."
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11 Ɛnnɛ wɔawo Agyenkwa a ɔne Kristo Awurade no ama mo wɔ Dawid kurom.
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1.24849
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mfa ayɛyɛdeɛ mmrɛ Ɔbaako a ɛsɛ sɛ wɔsuro noɔ no.
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mfa ayɛyɛde mmrɛ Ɔbaako a ɛsɛ sɛ wosuro no no.
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1.248328
|
6Yɛayɛ bɔne sɛdeɛ yɛn nananom yɛeɛ no;
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6Yɛayɛ bɔne sɛnea yɛn nenanom yɛe no;
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1.248269
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14Abɔdeɛ ɛnan no gyee so sɛ, "Amen!"
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Abɔde anan no gyee so se, "Amen!"
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1.248097
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Adeɛ a wɔyɛeɛ yi sii sɛdeɛ ɛbɛyɛ a Atwerɛsɛm a ɛka sɛ,
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Ade a wɔyɛɛ yi sii, sɛnea ɛbɛyɛ a Kyerɛwsɛm a ɛka se,
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1.248018
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Nnwoma ahodoɔ a menyaa mmoa firii mu.[sesamu]
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Nnwoma a menyaa mmoa firii mu.[sesamu]
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1.247914
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14Mpanimfoɔ ntena kuropɔn apono ano bio;
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14Mpanyimfo ntena kuropɔn apon ano bio;
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1.247602
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Deɛ asraafoɔ no yɛeɛ ne no.
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Nea asraafo no yɛe ne no.
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1.247446
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mɛyi wo nneduafoɔ afiri amena a nsuo nni mu.
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meyi wo nneduafo afi amoa a nsu nni mu mu.
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1.247308
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anaa mo hyeɛ afɔdeɛ a ɛwɔ mʼanim daa no ho.
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anaa mo hyew afɔre a ɛwɔ mʼanim daa no ho.
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1.247164
|
te sɛ abɔdeɛ a ɛwɔ ɛpo mu a wonni sodifoɔ.
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te sɛ abɔde a ɛwɔ po mu a wonni sodifo.
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1.246796
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38Misraim ani gyeeɛ ɛberɛ a wɔkɔeɛ,
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38Misraim ani gyei, bere a wɔkɔe,
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1.246669
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Soboɔ bɛdi mu ɛberɛ a nnipa baanu anaa baasa abɛdi adanseɛ.
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Bio, "Odwumayɛfoɔ akatua fata no!" 19Ntie asɛmmɔne a obi ka to ɔpanin bi so no, gye sɛ adansefoɔ baanu anaa baasa de saa asɛm no bɛto wʼanim.
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1.246618
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22"Mmerɛ dodoɔ a asase da so wɔ hɔ yi,
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22"Mmere dodow a asase da so wɔ hɔ yi,
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1.246256
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13Apono mmiɛnsa wɔ apueeɛ; mmiɛnsa wɔ anafoɔ; mmiɛnsa wɔ atifi ɛnna mmiɛnsa wɔ atɔeɛ.
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13 Ɛfa biara na apon abiɛsa na ɛwɔ hɔ - abiɛsa wɔ apuei; abiɛsa wɔ anafo; abiɛsa wɔ atifi ɛnna abiɛsa wɔ atɔe.
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1.246061
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14Abɔdeɛ ɛnan no gyee so sɛ, "Amen!"
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Na abɔde ateasefo baanan kɔso ka sɛ Amen (Ԑnyɛ hɔ).
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1.245872
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Me ne wo bԑ sa akↄ si ewieyi
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Me ne wo bɛ kɔ akosi ɛwieyɛ
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1.245175
|
18Yohane asuafoɔ kɔbɔɔ no deɛ asi no nyinaa ho amaneɛ.
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18 Yohane asuafo kɔbɔɔ no nea asi no nyinaa ho amanneɛ.
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1.244893
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19Mebisa bio sɛ, Israelfoɔ te aseɛ anaa wɔante aseɛ?
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Mibisa bio se, na Israelfo nnim anaa?
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1.2446
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14Ɛfiri sɛ, yɛnni atenaeɛ a ɛwɔ hɔ daa wɔ asase yi so.
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14 Efisɛ, yenni atenae a ɛwɔ hɔ daa wɔ asase yi so.
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1.244515
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Obiara mma Agya no nkyԑn gye sԑ ᴐnam Me so.
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Obiara mma Agya no nkyɛn gye sɛ ɔnam me so.'"
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1.244299
|
ɔfirii ha berɛ bɛn?
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berɛ bɛn na ɔfirii ha?
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1.244077
|
sɛ ɔdane ne ho kɔ anafoɔ fam a, mʼani nhye ne ho.
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sɛ ɔdan ne ho kɔ anafo fam a, mʼani nhye ne ho.
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1.243825
|
mʼatamfoɔ nhyɛsoɔ nti?"
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mʼatamfo nhyɛso nti?"
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1.243477
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28Ɛfiri sɛ Awurade bɛyɛ ntɛm, na sɛdeɛ ɛteɛ biara,
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28Efisɛ Awurade bɛyɛ ntɛm, na sɛnea ɛte biara no,
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1.243187
|
6Owia renhye wo wɔ awiaberɛ mu,
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6Owia rensɛe wo wɔ adekyee mu,
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1.242525
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Bieko, saa bɛle Kelaese ɛdeɛ a, ɛnee amgba bɛle Ebileham abozoamra."
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Bio nso, sɛ moyɛ Kristo dea a, ɛnde na moyɛ Abraham asefo ampa."
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1.24233
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sɛ ɔrebu ne nkurɔfoɔ atɛn;
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sɛ ɔrebu ne nkurɔfo atɛn;
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1.242232
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w'ayε nhyehyεe bi ama wo
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W'ayε nhyehyεe bi ama wo
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1.241248
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wɔde ogya bɛhyɛ nʼasɔredan mu ayɛyɛdeɛ nyinaa.
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wɔde ogya bɛhyew nʼasɔredan mu ayɛyɛde nyinaa.
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1.241219
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Imɔso aberɛ mɔ a fo mɔ, ɔ laa ba fɛye asɛ.
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Ɛbɛma Woahu Nea Worehwehwɛ No Ntɛm
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1.241205
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Ndoboa mɔɔ bɛfi bɛ ɛhulolɛ nu bɛye la yɛɛ yɛfa yɛyɛ ɛhye mɔ amuala a.
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, Ye 4:11 ɛ. ninyɛne kɔsɔɔti, wɔ ɛhulolɛ zo
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1.240976
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18deɛ anyansafoɔ apae mu aka,
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18nea anyansafo apae mu aka,
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1.24097
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"Ngakula, bɛdie bɛ awovolɛ wɔ debie biala anu, ɔluakɛ ɛhye a sɔ Awulae anye a."
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"Mma, muntie mo awofo asɛm ade nyinaa mu, na eyi na ɛsɔ ani Awurade mu."
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1.240916
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29Deɛ mekyerɛ ne sɛ, anuanom, ɛberɛ a aka sua.
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29 Nea mekyerɛ ne sɛ, anuanom, bere a aka sua.
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1.240873
|
8Enti, twɛn me," sɛdeɛ Awurade seɛ nie,
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8Enti twɛn me," sɛnea Awurade se ni,
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1.24086
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14na ɔnim sɛdeɛ wɔyɛɛ yɛn,
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14na onim sɛnea wɔyɛɛ yɛn,
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1.239968
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Siane mɔɔ bɛfa bɛboka nwo fane nsuu wɔ ɛvolɛ 19 biala anu la
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Ɔsram a wɔde ka ho mpɛn 7 wɔ mfe 19 biara mu
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1.23966
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wɔwuwu na wɔsane kɔ mfuturo mu.
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wowuwu na wɔsan kɔ mfutuma mu.
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1.239058
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1Ao Awurade, hwɛ sɛdeɛ mʼatamfoɔ dɔɔso fa!
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1Awurade, hwɛ sɛnea mʼatamfo dɔɔso fa!
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1.239037
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14Wɔsii kuro no afasuo sii aboɔ dumienu a wɔatwerɛ Odwammaa no asomafoɔ dumienu no din wɔ so no so.
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14 Wosii kurow no afasuw sii abo dumien a wɔakyerɛw Oguammaa no asomafo dumien no din wɔ so no so.
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1.238564
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Duzu a bɛkilehile wɔ wɔ sukulu ɛkɛ a?
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Dɛn na musua wɔ sukuu?
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1.238471
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wʼabɔdeɛ ahyɛ asase so ma.
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wʼabɔde ahyɛ asase so ma.
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1.23793
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Wʼabofuhyeɛ yɛ kɛseɛ sɛdeɛ wo ho suro teɛ.
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Wʼabufuwhyew kɛse te sɛnea wo ho suro te.
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1.236511
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7Tene wo nsa firi soro bra fam;
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7Teɛ wo nsa fi ɔsoro bra fam;
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1.236408
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Enti, Kenifoɔ no twee wɔn ho firi Amalekfoɔ no ho.
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Enti Kenifo no twee wɔn ho fi Amalekfo no ho.
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1.235819
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16Enti, ɛda no ara, Esau sane nʼakyiri kɔɔ Seir.
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16Enti da no ara, Esau san nʼakyi kɔɔ Seir.
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1.235604
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na wɔbɛdi nʼahyɛdeɛ so.
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Na wɔtie n'ahyɛde.
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1.235554
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Wʼadwadifoɔ yɛ ewiase mu nnipa titire.
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W'adwumayɛfo yɛ wiase mu nnipa titiriw.
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1.235465
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Saa ɛberɛ korɔ no ara mu, abɔfra no ho tɔɔ no!
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Abofra no ho tɔɔ no saa bere no ara mu!
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1.235442
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25Ɔno na ɔma abɔdeɛ biara aduane.
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25Ɔno na ɔma abɔde biara aduan.
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1.235298
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"Mmamaa Mɛla buluku ɛhye fi ɛ nloa anu, emomu ɔwɔ kɛ ɛkenga na ɛdwenledwenle nwo alehyenlɛ nee aledwolɛ, amaa wɔanlea wɔali debie biala mɔɔ bɛhɛlɛ ye wɔ nu la azo; ɛhye bamaa yeawie wɔ boɛ na wɔabɔ wɔ ɛbɛla nrɛlɛbɛ nu."
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"Mma Mmara nhoma yi mmfi w'anom, na mmom kenkan na dwinnwen ho awia ne anadwo na woadi nea wɔakyerɛw wom nyinaa so pɛpɛɛpɛ.
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1.234418
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na fa yɛn aka firi yɛn, sɛdeɛ yɛdɛ firi wɔn a wɔde yɛn aka.
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na fa yɛn mfomsoɔ kyɛ yɛn sɛdeɛ yɛn nso yɛde kyɛ wɔn a wɔfom yɛn.
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1.234046
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mekasaeɛ no, obiara antie.
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mekasae no, obiara antie.
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1.232771
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Wɔyɛɛ deɛ ɔkaeɛ no wieeɛ no, 34ɔkaa sɛ, "Monyɛ saa ara bio!"
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Wɔyɛɛ nea ɔkae no wiei no, 34ɔkae se, "Monyɛ saa ara bio!"
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1.232757
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6Ɔsane firii adi bɛyɛ nnomum berɛ mu, kɔhunuu sɛ nnipa bi gyinagyina hɔ.
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6Ɔsan fii adi bɛyɛ nnɔnnum bere mu, kohuu sɛ nnipa bi gyinagyina hɔ.
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1.232741
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Yesu kae sԑ:" Meyԑ ᴐkwan ne nokware ne nkwa na obiara ntumi mma Agya no nkyԑn gye sԑ ᴐnam Me so-Yohane 14:6.
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Gyisɛse hanle kɛ: "Mame a mele adenle ne, nɔhalɛ ne, nee ngoane ne a; awie biala ɛnrɛhola Selɛ ne ɛkɛ ne kɔ kyesɛ ɔdua me nwo zo."
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1.232487
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2"Madɔ mo," sɛdeɛ Awurade seɛ nie.
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2"Madɔ mo," sɛnea Awurade se ni.
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1.232453
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Soboɔ bɛdi mu ɛberɛ a nnipa baanu anaa baasa abɛdi adanseɛ.
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Bio, "Odwumayɛni akatua fata no!" 19Ntie asɛmmɔne a obi ka to ɔpanyin bi so no, gye sɛ nnansefo baanu anaa baasa de saa asɛm no bɛto wʼanim.
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1.232433
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Duzu ati a amaneɛnwunlɛ ɛbu zo wɔ ewiade a?
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Adɛn nti na amanehunu adɔɔso wɔ wiase saa?
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1.232424
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Bɛdule Ɛnwomenlelielɛ kenle ne bɛziele ɛkɛ bɛmanle abusua ɛzonlenlɛ, nzɛlɛlɛ, nee Nyamenle Mɛla ne anwo ɛdwenledwenlenlɛ.
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Na ɛsɛ sɛ wɔde Homeda no yɛ abusua som, bɔ mpae, na wodwinnwen Onyankopɔn Mmara ho.
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1.232302
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Wɔwe me nkurɔfoɔ sɛdeɛ nnipa di aduane.
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Wɔwe me nkurɔfoɔ te sɛ deɛ nnipa di aduane.
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1.232077
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4Nom asuo no mu nsuo, na di deɛ anene no de bɛbrɛ wo, ɛfiri sɛ, mahyɛ sɛ wɔmmrɛ wo aduane."
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4Nom asu no mu nsu, na di nea kwaakwaadabi no de bɛbrɛ wo, efisɛ, mahyɛ sɛ wɔmmrɛ wo aduan."
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1.231957
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mede mʼano bɛda wo nokorɛdie adi awoɔ ntoatoasoɔ nyinaa mu.
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mede mʼano bɛda wo nokwaredi adi awo ntoatoaso nyinaa mu.
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1.231701
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29Deɛ mekyerɛ ne sɛ, anuanom, ɛberɛ a aka sua.
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29Nea mekyerɛ ne sɛ, anuanom, bere a aka no sua.
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1.231455
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na ɛyɛɛ me sɛdeɛ wɔrewie me.
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na ɛyɛɛ me sɛnea wɔrewie me.
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1.231447
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tua ahantanfoɔ ka sɛdeɛ ɛfata wɔn.
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na fa nea ɛfata wɔn san bra wɔn so.
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1.231039
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Yei nso maa deɛ adiyifoɔ no kaeɛ sɛ, "Wɔbɛfrɛ no Nasareni" no baa mu.
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Eyi nso maa nea odiyifo no kae se, "Wɔbɔfrɛ no Nasaretni no baa mu.
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1.230871
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14Woama nnipa ayɛ sɛ nsuomnam a ɛwɔ ɛpo mu,
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14Woama nnipa ayɛ sɛ nsumnam a ɛwɔ po mu,
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1.230667
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ɛyɛ amanehunu ne ɔsɛeɛ ɛda,
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ɛyɛ ahoyeraw ne ɔyaw da;
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1.230595
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6Festo dii bɛyɛ nnawɔtwe anaa dadu ansa na ɔresane aba Kaesarea.
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6 Festo dii bɛyɛ nnawɔtwe anaa dadu ansa na ɔresan aba Kaesarea.
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1.230351
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Ɛbahola wɔamaa bɛ ɛleka mɔɔ bɛbala anzɛɛ aleɛ ɔ?
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Anaasɛ sɛ ͻkͻm de wo paa na wote aduane baako pɛ no ara na w'amee?
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1.2303
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ɛnhye nʼatadeɛ anaa?
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nhyew nʼatade ana?
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1.230271
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sɛdeɛ Awurade hyɛɛ wɔn no,
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sɛnea Awurade hyɛɛ wɔn no,
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1.229928
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12Monsane nkɔ mʼaban mu, Ao nneduafoɔ a mowɔ anidasoɔ;
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12Monsan nkɔ mʼaban mu, nneduafo a mowɔ anidaso;
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1.229396
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deɛ ɔwɔ tumi sene ɛpo nworosoɔ.
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nea ɔwɔ tumi sen po nworoso,
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1.229041
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Ye neazo ne ɛmaa menwu kɛ saa awie bɛlɛ ɔ nwo aze wɔ Nyamenle anyunlu, ɔdie ndeanlɛ ɔto nu a, ɔnyia nyilalɛ dɔɔnwo!"
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na wɔn a wɔnu wɔn ho no, wɔde tenenee bɛgye wɔn.
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1.228942
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Yɛ no foforɔ wɔ yɛn mmerɛ so.
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Yɛ no foforo wɔ yɛn mmere so.
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1.228848
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ɛno na woakora ama wɔn a wɔsuro woɔ no;
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ɛno na woakora ama wɔn a wosuro wo no
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1.228692
|
21Enti, ɛberɛ a amrado no sane bisaa wɔn sɛ, "Nnipa baanu yi mu hwan na mopɛ nɛ megyaa no ma mo?"
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21Enti amrado no san bisaa wɔn se, "Nnipa baanu yi mu hena na mopɛ sɛ migyaa no ma mo?"
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1.228529
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6Mʼani bɛkɔ anokwafoɔ a wɔwɔ asase no soɔ no so
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6Mʼani bɛkɔ anokwafo a wɔwɔ asase no so no so
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1.228486
|
16Nanso, awoɔ ntoatoasoɔ a ɛtɔ so ɛnan no mu, wʼasefoɔ bɛsane aba saa ɔman yi mu bio.
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16Nanso awo ntoatoaso a ɛto so anan no mu, wʼasefo bɛsan aba saa ɔman yi mu bio.
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1.228431
|
5"Ɔsane kɔɔ owigyinaeɛ ne nnɔnmiɛnsa ɛberɛ mu kɔbɔɔ nnipa foforɔ paa ne wɔn yɛɛ nhyehyɛeɛ korɔ no ara bi.
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"Ɔsan kɔɔ owigyinae ne nnɔn abiɛsa bere mu kɔbɔɔ nnipa foforo paa ne wɔn yɛɛ nhyehyɛe koro no ara bi.
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1.227832
|
9Ampa ara, ne nkwagyeɛ bɛne wɔn a wɔsuro no,
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9Ampa ara, ne nkwagye bɛn wɔn a wosuro no,
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1.227777
|
Ɛberɛ a wɔde Ben-Hadad baeɛ no, Ahab ma ɔkɔtenaa ne teaseɛnam mu.
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Bere a wɔde Ben-Hadad bae no, Ahab ma ɔkɔtenaa ne teaseɛnam mu.
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1.227735
|
7Mo deɛ nnipa tan mo a ɛnyɛ yie, nanso me deɛ wɔtan me a ɛyɛ yie, ɛfiri sɛ, daa meka bɔne a wɔyɛ no kyerɛ wɔn.
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7Mo de, nnipa tan mo a ɛnyɛ ye, nanso me de wɔtan me a ɛyɛ ye, efisɛ daa meka bɔne a wɔyɛ no kyerɛ wɔn.
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1.227192
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oh no no no, that's easy, so easy for me...
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Yeah It's So Easy, Easy for Me
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1.226974
|
7Ɛbɛyɛ ɛda soronko a ɛnni awiaberɛ anaa anadwo, ɛda a Awurade na ɔnim.
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7Ɛbɛyɛ da sononko a enni awia anaa anadwo, da a Awurade na onim.
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1.225904
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Nyamenle biala nee bɛ ɛdeɛ ne ɛnzɛ.'
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Nyame Biara Ntse Wo
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1.225897
|
Bɛha bɛhile menli dɔɔnwo kɛ Nyamenle ndenle ne mɔ le fealera nu debie anzɛɛ ɔmaa menli wu - bɔbɔ ngakula - amaa yeava bɛ yeahɔ ɔ nwo lɔ wɔ anwuma.
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Wɔka kyerɛ nnipa pii sɛ Onyankopɔn akwan yɛ nea wontumi nte ase, anaasɛ Onyankopɔn na ɔma nnipa a mmofra ka ho wuwu, sɛnea ɛbɛyɛ a obenya wɔn ne wɔn atra soro.
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1.225599
|
firi ananafoɔ nsam,
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fi ananafo nsam,
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1.225551
|
16Ɔno na ɔdii ne nkurɔfoɔ anim wɔ ɛserɛ no so.
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16Ɔno na odii ne nkurɔfo anim wɔ sare no so.
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1.22499
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na wɔn mma nso nka nkyerɛ awoɔ ntoatoasoɔ a ɛdi soɔ no.
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na wɔn mma nso nka nkyerɛ awo ntoatoaso a edi so no.
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1.224919
|
56Maria tenaa Elisabet nkyɛn bɛyɛ abosome mmiɛnsa ansa na ɔresane akɔ ne kurom.
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56 Maria tenaa Elisabet nkyɛn bɛyɛ asram abiɛsa ansa na ɔresan akɔ ne kurom.
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1.224843
|
Anrɛɛ bɛ muala bɛbahola bɛadɛnla aze dahuu wɔ anyelielɛ nu wɔ azɛlɛ ye azo.
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Na moatena ase nna tenten na asi mo yie wɔ asase a morebɛkɔ akɔtena so no so."
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1.224821
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na fa yɛn aka firi yɛn, sɛdeɛ yɛdɛ firi wɔn a wɔde yɛn aka.
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sɛdeɛ yɛde wɔn a wɔfom yɛn no bɔne kyɛ wɔn no.
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1.224717
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2 Bɛhɔ zo bɛboa bɛ nwo ngoko wɔ ninyɛne mɔɔ anu yɛ ɛlomboɛ la anu, na ɔlua zo bɛali Kelaese mɛla ne azo.
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"Monkɔ so mmoa mo ho mo ho wɔ nneɛma a emu yɛ duru mu na monam so awie Kristo mmara no so di." - GAL.
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1.224589
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8Ɛberɛ a Israel somm anyame foforɔ no,
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8Bere a Israel som anyame foforo no,
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Akan-Twi_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: Akan-Twi_Sentence-Pairs
- Number of Rows: 76666
- Number of Columns: 3
- Columns: score, Akan, Twi
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).Akan: The first sentence in the pair (language 1).Twi: 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
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Size of downloaded dataset files:
7.28 MB
Size of the auto-converted Parquet files:
5.12 MB
Number of rows:
76,666