Africa Emotion Datasets
Collection
The collection contains emotion-labeled text data for 42 African languages
•
45 items
•
Updated
Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Languages:
Fon
Size:
10K - 100K
License:
Dataset Viewer
Fon
stringlengths 10
211
| emotion
stringclasses 7
values |
|---|---|
Le Livre bleu,
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neutral
|
Kpɔ lé àzan ao Bibla do keŋ akpɔ Mawu Nyɔ kpukpuiwo.
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neutral
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Ani Mɛi ni Egboi lɛ Yahiɔ He Ko?
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anger
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Mɛ é wa mɔ de mɔnɔ nɔ fyéé, yi
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fear
|
Mɛni kɔkɔ bɔmi bɔfohi enyɔ ɔmɛ kɛ ha Lot?
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fear
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Mɛni he je nɛ suɔmi nɛ ngɛ Mawu kɛ e Bi ɔ a kpɛti ɔ mi wa wawɛɛ ɔ?
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disgust
|
jié luó bō jié luó bō wèi yī hē pó pó,
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neutral
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Ee zɛkpá bo bú lɛ é,
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anger
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Ye yí wɛn ɔ, ye sixu gán;
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neutral
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Mawu kpl'ɛ sín ablu mɛ,
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disgust
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Mawu de Noa ke e kpɛ lɛ ɔ bɔnɛ nyu be nyɛe maa sɛ mi.
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neutral
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Mɛɛ gbɛ nɔ Lot ŋa lɛ sane lɛ ji kɔkɔbɔɔ kɛhã wɔ ŋmɛnɛ?
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disgust
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Se mɛni heje nɛ Yosef kɛ Maria lɛɛ a be hiɛ ɔ?
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neutral
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Mɛdídá sín hwe wɛ ná cí!
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disgust
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ni komɛ hu beɔ, se wa kpa we.
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joy
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Mi ni gbí dɔn ganji, ajɔ mitɔn sɛkpɔ.
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neutral
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Wa keɔ Mawu ní kɛ tsɔɔ kaa wa suɔ lɛ.
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sadness
|
Mawu de ke: 'Nyɛɛ ba ye ngɔ.
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disgust
|
La Kpaakpo lɛ Tamɔ Gehena, ni Ji Hinom Jɔɔ lɛ Nɔŋŋ
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anger
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E ji sane kpakpa nɛ ngɛ Baiblo mi;
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neutral
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Lɔɔ he ɔ, i muɔɔ mɛ, nɛ i ba pu mɛ ngɛ ye bo tsu ɔ mi.'
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joy
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Duzu ati a ɛ nye die kɛ Nyamenle duma la ɛ nwo zo na ɛkulo kɛ ɛka mɔɔ ɔkile la anwo edwɛkɛ ɛkile awie mɔ ɛ?
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anger
|
Bɛye Nyamenle ɛlɔlɛ nee ye gyima mgbole ne mɔ ayɛlɛ
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joy
|
Ke Mawu ko ngɛ nɛ e ngɛ he wami pe nɔ tsuaa nɔ ɔ, mɛni he je nɛ e nyɛ we nɛ e bu nimli kpakpahi a he konɛ haomi nɛ ko ba a nɔ ɔ?
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anger
|
Mɛtɛnkpɔn lɛ wá ɔ,
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neutral
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Suzu mɔɔ sɛkɛlɛneɛ adenle zo nɔma mɔɔ wɔ Baebolo ne anu abo kile la neazo bie mɔ anwo, na kpondɛ kɛzi bɛle ngakyile bɛfi nɔma nwo mgbondabulɛ nwo la.
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neutral
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Kɛmaje Mɔ Ko Kɛmaje Mɔ Ko Bi Kpakpa, kɛ Bi Fɔŋ
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neutral
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naa mà konɔ kan ma yo panla gbɔn we!"
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anger
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Yɛnŋɛlɛ lì dunruya ŋa wi fyɔnwɔ fɛnnɛ pe wɔ,
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disgust
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Mɛnɔ ji bimwɔyo nɛ ngɛ foni ɔ mi ɔ, nɛ mɛnɔ nine nguɛ he e pɛtɛ ɔ?
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joy
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Káád sé ésuud mɛ nzɔm.'
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neutral
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Ebuɔ amɛ fɛɛ jalɔi,
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neutral
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Mɛɛ gbɛ nɔ asafoi baanyɛ awo mɛi ni egbɔlɔ ni yɔɔ amɛteŋ lɛ ahiɛ nyam?
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disgust
|
na tɛgɛ wi na,
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neutral
|
Na ka nli ngba ɔsu ni, amii lɛnɔ bɛdubulie ngba.
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neutral
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Se gbi ɔ de lɛ ke: 'Moo jɔɔ níhi nɛ Mawu tsu he ɔ tsɛmi ke a he tsɔ we.'
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neutral
|
Mɛɛ tsɔsemɔ krɛdɛɛ ato he gbɛjianɔ ahã mɛi ni kɛ amɛbe fɛɛ shiɛɔ Maŋtsɛyeli lɛ he sane lɛ?
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neutral
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Ni komɛ ke Mawu ngɛ siɔɔ,
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neutral
|
"Enɛ ɔ he tutuutu nɛ Mawu Bi ɔ ba a nɛ, konɛ níhi nɛ Abosiami tsu ɔ, e ba kpata lɛ tsuo hɛ mi."
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neutral
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K'ayi la n'igwé n'ikpe-azu,
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neutral
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Kɛì Nyɔŋmɔ yeɔ je lɛ nɔ lɛ, mɛni hewɔ amanehulu yɔɔ mli lɛ?
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disgust
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Ha nɛ waa hyɛ bɔnɛ Mawu pee enɛ ɔ ha.
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neutral
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Mɛɛ gbɛ nɔ Mose tsɔ ejie hemɔkɛyeli kɛ ekãa kpo?
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neutral
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Putin il é bo !
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anger
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Nyɔnuví ɔ ba tawun bo na d'alɔ ɛ.
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disgust
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itèdzú ɔdzɔ bíbí
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neutral
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Mɛni heje nɛ ní yayamihi ngɛ nɔ yae ngɛ je ɔ mi wawɛɛ amlɔ nɛ ɔ pe be ko nɛ be ɔ?
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fear
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Xógbe tɔn lɛ gblewu mì tawun.
|
sadness
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Jije hiɔwe kɛ zugba a je kɛ ba?
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neutral
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Dieu est Révélation.
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neutral
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Ye na kpé nukún dó ayikúngban ɔ kpo kanlin lɛ kpo wu.
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anger
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hɔ ba gɔnnɛ faire du bien
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neutral
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Chɛɛ Fa Yataa, an mbe daun fenɛ chɛndɛ chɛndɛ be wo ma, a ka banda bu ɔ.
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neutral
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Mɔka aalɔ banama gi bɛlɔ mɛ ɛ.
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neutral
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wlɛnwín e ye nɔ zán lɛ é mɛ?
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neutral
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Sanngɛ Salomɔn wa jali nvle uflɛ nun bla kpanngban mɔ be sɔ amuin'n.
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neutral
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Nɛ ni komɛ hu heɔ yeɔ kaa adesahi tsuo sɔ ngɛ Mawu hɛ mi.
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fear
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Mɛni ji Mawu Matsɛ Yemi ɔ, nɛ mɛnɔ ji e nya Matsɛ?
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surprise
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konaa Yɛnŋɛlɛ làa Yinnɛkpoyi yɔn fɔlɔ na kɔn,
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neutral
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Mawu nɔ yemi ɔ ma kpata je ɔ mi nɔ yemihi tsuo a hɛ mi.
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neutral
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Mɛni hewɔ mɔ ko bɛ gbonyo bu lɛ mli lɛ?
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neutral
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Ejaakɛ nibii fɛɛ ni nakai mɔ lɛ feɔ lɛ, nomɛi nɔŋŋ Bi lɛ hu feɔ.
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anger
|
Menli nwunle daselɛ mɔɔ kile kɛ Nyamenle ɛlɛyila Nowa ɛdeɛ, noko bɛgolole ɔ nwo na bɛandie ye edwɛkɛ
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neutral
|
Benɛ Satan ka Yesu ɔ, anɛ e ngɔ lɛ kɛ ya sɔlemi we ɔ nitsɛnitsɛ, aloo e je sɔlemi we ɔ kɛ tsɔɔ lɛ ngɛ nina mi?
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neutral
|
Namɔ ji awula ni yɔɔ mfoniri lɛ mli lɛ, ni mɛni gbekɛ yoo fioo lɛ feɔ yɛ awula lɛ shia?
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neutral
|
Uwien baba ŋa ñí la, ŋmɛ li fre kí fère binib biʼbiɛre?"
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neutral
|
Mɛɛ gbɛ nɔ wɔbaanyɛ wɔná Noa sane lɛ he sɛɛ ŋmɛnɛ?
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neutral
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Mɛni hewɔ Mose bi Nyɔŋmɔ gbɛi be mli ni ele gbɛi lɛ momo lɛ?
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neutral
|
Nɔ inɔ ku fɔi í jɛ ti tenku,
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sadness
|
Hii anɔkwafoi nyiɛ maŋbii lɛ ahiɛ
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surprise
|
Kɛmaje Mɔ Ko Kɛmaje Mɔ Ko Ato Wɔhe Gbɛjianɔ Koni Wɔsɔmɔ 'Toiŋjɔlɛ Nyɔŋmɔ Lɛ'
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disgust
|
Mɛnɔ ji Mawu Matsɛ Yemi ɔ nya matsɛ, nɛ mɛni Matsɛ Yemi ɔ ma tsu?
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neutral
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Un sixu kpé nukún dó lanmɛ ce wu ganji gbɔn . . .
|
sadness
|
Nɛ ɛnɛ lɛma de dedemɔ ha tɛ mbwa ha ngimɔ ka sila ɛnɛ ngoya.
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neutral
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Yɛnŋɛlɛ li lasiri wi yɛn kpoyi,
|
sadness
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Sane bimihi: Kɛ bɔfohi plɛ kɛ fia Yesu fɔmi ɔ he adafi ha kɛɛ?
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surprise
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Só lɛ, xù kpo hwesivɔ kpo;
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neutral
|
Mawu Matsɛ Yemi ɔ, aloo e nɔ yemi ɔ maa hi hiɔwe kɛ ye zugba a tsuo nɔ.
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disgust
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Kɛ o ma plɛ kɛ le kaa Mawu ha mo hiɔwe he hɛ nɔ kami loo zugba a nɔ hɛ nɔ kami ha kɛɛ?
|
fear
|
Mɛɛ gbɛ nɔ nɔ ni yɔɔ Kristofonyo ko tsui mli lɛ baanyɛ aye lɛ awui?
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neutral
|
?Ngue like yɛlɛ nga ɔ blabla waka'n wun desɛn'n su lɛ'n? ?Yɛ ngue ti yɛ Zoova seli Moizi kɛ ɔ fa sie i lɛ ɔ?
|
neutral
|
Ni bɔfoi lɛ ha amɛ hetoo akɛ: 'Esa akɛ wɔboɔ Nyɔŋmɔ moŋ toi akɛ nɔyelɔ fe gbɔmɛi.'
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disgust
|
Mɛni blɔ nɔ o maa gu kɛ ná sɛ gbi nɛ Mawu kɛ ha adesahi, nɛ ngɛ Baiblo ɔ mi ɔ amlɔ nɛ ɔ kɛ hwɔɔ se ɔ he se?
|
neutral
|
Peter jɛ huzuhuzu jí.
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neutral
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Sa tɛ kun o lɛ'n, e tɔ nun ndɛndɛ kpa,
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neutral
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Mɛɛ nibii komɛi baanyɛ awa bo ni okane nɔ ni aŋma lɛ pɛpɛɛpɛ ni eje kpo?
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neutral
|
Biblu'n nun ndɛ: Moizi nin Aarɔn be o Faraɔn lɔ - Zoova i lalofuɛ'm be ɛntɛnɛti adrɛsi nga sran ngba si i'n
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neutral
|
Anɛ o Mawu ɔ nɛ o sɔmɔɔ lɛ ɔ kpɔ mo kɛ je jata amɛ a dɛ mi lo?'
|
fear
|
Azɔn nukɔntɔn e un mɔ laglasi linfin é nɛ.
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disgust
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Ni komɛ heɔ yeɔ kaa Mawu jɔɔ nihi pɔtɛɛ komɛ aloo e gbiɛ nihi pɔtɛɛ komɛ.
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neutral
|
shí ài ài qí jiāng bà xī ,jié yōu lán ér yán zhù ;
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disgust
|
Zinkpo tɔn jinjɔn hwɛjijɔ jí,
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neutral
|
Fã nɛ ji What's New ɔ ma ha nɛ o na ní hehi nɛ a kɛ wo nɔ ngɛ gbi nɛ o hla a mi.
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neutral
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Atsɔ hɛ gobɛ alã alɔ sueawo,
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neutral
|
Enɛ ha Farao, ni ji Mizraim maŋtsɛ lɛ mli fu.
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neutral
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A na mɔ lee gbɛzán Jezu tɔn kpo kú tɔn kpo sixu hɛn lè wá nú we gbɔn é.
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neutral
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Il a regardé: E mɔ nyɛ kpɔ ɛ
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surprise
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Nyamenle lɛ amodinli dɔɔnwo, mɔɔ Tumivolɛ Bedevinli, Bɔvolɛ nee Awulae boka nwo a.
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neutral
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Ne ɔ tɔgɛ sa ɔmɔ yɛɛ,
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neutral
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Nùkplɔnmɛ elɔ lɛ sixu d'alɔ hwi lɔ.
|
neutral
|
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in Data Studio
Fon Emotion Analysis Corpus
Dataset Description
This dataset contains emotion-labeled text data in Fon for emotion classification (joy, sadness, anger, fear, surprise, disgust, neutral). Emotions were extracted and processed from the English meanings of the sentences using the model j-hartmann/emotion-english-distilroberta-base. The dataset is part of a larger collection of African language emotion analysis resources.
Dataset Statistics
- Total samples: 34,915
- Joy: 3116 (8.9%)
- Sadness: 2218 (6.4%)
- Anger: 2801 (8.0%)
- Fear: 2005 (5.7%)
- Surprise: 2485 (7.1%)
- Disgust: 3113 (8.9%)
- Neutral: 19177 (54.9%)
Dataset Structure
Data Fields
- Text Column: Contains the original text in Fon
- emotion: Emotion label (joy, sadness, anger, fear, surprise, disgust, neutral)
Data Splits
This dataset contains a single split with all the processed data.
Data Processing
The emotion labels were generated using:
- Model:
j-hartmann/emotion-english-distilroberta-base - Processing: Batch processing with optimization for efficiency
- Deduplication: Duplicate entries were removed based on text content
Usage
from datasets import load_dataset
# Load the dataset
dataset = load_dataset("michsethowusu/fon-emotions-corpus")
# Access the data
print(dataset['train'][0])
Citation
If you use this dataset in your research, please cite:
@dataset{fon_emotions_corpus,
title={Fon Emotions Corpus},
author={Mich-Seth Owusu},
year={2025},
url={https://huggingface.co/datasets/michsethowusu/fon-emotions-corpus}
}
License
This dataset is released under the MIT License.
Contact
For questions or issues regarding this dataset, please open an issue on the dataset repository.
Dataset Creation
Date: 2025-07-04 Processing Pipeline: Automated emotion analysis using HuggingFace Transformers Quality Control: Deduplication and batch processing optimizations applied
- Downloads last month
- 10
Size of downloaded dataset files:
1.32 MB
Size of the auto-converted Parquet files:
1.32 MB
Number of rows:
34,915