Africa Emotion Datasets
Collection
The collection contains emotion-labeled text data for 42 African languages
•
44 items
•
Updated
Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Languages:
Kabiyè
Size:
10K - 100K
License:
Dataset Viewer
Kabiye
stringlengths 10
261
| emotion
stringclasses 7
values |
|---|---|
wunlunaŋa wi yaa ka mbele pe wa wi kalige kɛɛ ki na pe pye fɔ:
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neutral
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Nɛɛ tosa yɛ mi mɛŋndaŋ ma muuliaŋ nda choo mulukɛlɛɛ?
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anger
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Cɛɛlɛ mbele pàa ku,
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anger
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Na ɔku ɔmmɔ geen muudie kenye taasiku-mi lɛlɔ.
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fear
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Wala Ji Naakpɛɛ Nii
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surprise
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yuu peparae kaeya nao suu pyao karo.
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disgust
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waasa u kana yeli kɛ, u kana mɛnni kɛ,
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anger
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taa wwiuit,
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neutral
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Muwi mìla pye na penjara to naa tɛ wi kaan wi yeri lɛgɛrɛ,
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sadness
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Kunli nee yelɛ nee bɛ mra a le ekpunli mɔɔ bɔ sua ɛkyekyelɛ bo anzɛɛ ekpunli mɔɔ tɛlɛ yɛ menli dɔɔnwo a, yemɔti ɔwɔ kɛ menli ekpunli ne nee maanle ne mɔɔ bɛwɔ nu la sinza bɛ.
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neutral
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Fɔɔ ka na se bii ma,
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neutral
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Azɛlɛ ne bakpakye na yeame menli ɛtanevolɛ ɛhye mɔ.'
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disgust
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waga si kaa we yɛɛ nawa ŋgbanni,
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neutral
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Nyɛ o nyɛ naŋ nɔ miŋ piɛi le ndu, yɛɛnɛ nɔ yɛ mbo wa nyɛ tasoo o yoomu naa niŋ?
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anger
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"Yaa kiti wi kɔɔn yaa yala kasinŋge ki ni pilige pyew.
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neutral
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Ba kɛnu yiyirɛ daaliɛriŋ ma nɛ, bɛɛ wiaa ba fa ŋaa daaliɛriŋ nɛ.
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fear
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Bani wee ya jomɔ yu,
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surprise
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Teleŋ naŋ ve kɔl te wo ɔɔ teleŋ naŋ wu ŋdiallo yaamɔɔwaa naa chiŋalaŋ naa ni.
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sadness
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Di ma nɛ ŋaa ŋii, ma ma jaŋ kɛŋ pulumuŋ a ma chaanɛ."
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anger
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Mɛni hewɔ wɔbaanyɛ wɔkɛɛ akɛ Noa, "jalɛ shiɛlɔ lɛ" tsu eshiɛmɔ nitsumɔ lɛ jogbaŋŋ lɛ?
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surprise
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Anɛ o he ye kaa ke waa kɛ Mawu mlaahi nɛ kɔɔ je mi bami he ɔ tsuɔ ní ɔ, wɔ nitsɛmɛ wa náa he se lo?
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anger
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Pyaaraa watan, Pak watan,
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neutral
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a kacɛn wà suu yɛɛ naga naa wa yɛnŋɛlɛ na:
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fear
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Baiblo nɛ wa maa kase daa,
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disgust
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Yawe Yɛnŋɛlɛ li yaa kari yaari mberi jaanri,
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neutral
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Sane ni oblanyo fioo Yeremia shiɛ lɛ wo maŋ onukpai lɛ amli la waa.
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neutral
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a wì suu konɔ li lɛ na kee,
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disgust
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Ma yaripɔrɔ fire lɔ ma ta maa ma yɛɛ poo,
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anger
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N we-ɛɛla bwa maa ɛa la, n Mɛɛ la kpegri nee mɛɛ ɛa asɛ aa di mɛ danseɛ.
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disgust
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na pe yaripɔrɔ ti woo nari waa,
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disgust
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yaa ye pɛnɛ pe sɛnrɛ ti nuru,
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neutral
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Alubi kama nɛ a ba,
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neutral
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Maa ii houni navoo hinda i yɛ kɔlɔgaala ma, kɛ bɛɛ i wote a ye tɔtɔmɛi.
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neutral
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Na tafɔ wi yaa mɔ wa,
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neutral
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Cha ma nikuu ka tatsi kuera ña nuu ñuu .
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anger
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naa Arɔn gbɔtangala na làa fyɛɛnrɛ fi li ni,
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neutral
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naapa twaapa waapa mwaapa aapa waapa waapa yaapa laapa yaapa chaapa vyaapa yaapa zaapa waapa kwaapa paapa mwaapa
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disgust
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Ke waa kɛ wa juɛmi maa ní kpakpahi nɛ nihi peeɔ ɔ nɔ ɔ, mɛni se wa ma ná?
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disgust
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Shi wemu kaa bi dan nɛ ni-i ge,
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neutral
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Bɛlbwa ta wone lawɔ, dɛkalkɛ dɛ o tɔpere ta tele mɔɔ.
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neutral
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ma fyɛɛlɛ maa sunlu,
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anger
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Te mibii lɛ baafee tɛŋŋ?" - Janet, United States.
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fear
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Asoo Nyamenle bu menli mɔɔ vi maanle bie anu la kɛ bɛle kpalɛ bɛtɛla maanle gyɛne ɔ?
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surprise
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No ji yiŋtoo kome hewɔ ni piŋmɔ babaoo yɔɔ lɛ.
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neutral
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Mɛni ji nike ní nɛ he jua wa nɛ Mawu ma ha nihi nɛ sa e hɛ mi ɔ, nɛ mɛni e sa kaa waa pee konɛ wa nine nɛ su nɔ?
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neutral
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Yɛnŋɛlɛ li tijinliwɛ mba pìla pye ma lara leele pe na,
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disgust
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nɛ mɛɛ su mu fɛni,
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neutral
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to wìla pye na sɔngɔrɔ ti na, na yuun fɔ:
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neutral
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Vvenɛ nfungala ɔlɔɔt 'wɔng baang ka lubbe ka kɛtɔm-a-lakpeke.
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anger
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ye pye ki mbajɛnmbɛlɛ paa piile yɛn.
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neutral
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paa pe ma kaa fyɔngɔ le kɛrɛ we,
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anger
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wunlunaŋa Salomɔ wo naa wi yarijɛndɛ lɛgɛrɛ tawa pi ni fuun ni,
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neutral
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Shi kɛji akɛ amɛye tso lɛ yibii lɛ eko lɛ, mɛni no baatsɔɔ? -
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neutral
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Eeish,ine kaaa kaaa tiyenayeni...
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fear
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na wiga pye kɛɛnrɛ lifɔ,
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neutral
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Nɔ hyɛmi níhi etɛ nɛ wa susu he ɔ tsɔɔ kaa Mawu nyɛɔ tsɔɔ níhi nɛ maa ba hwɔɔ se, nɛ e baa mi.
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neutral
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Te ŋ piɛi pɛ o nɛi bɛnda wo choo nduyɛ le nyɛm sɔviɔŋ, o cho nilaŋ yaŋɔɔ.
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anger
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Amrɔ nɛɛ eeba ebakpɛ eyiŋ yɛ sane ko ni he hiaa waa he.
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neutral
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Mɛɛ gbɛ nɔ ebaatsɔ kɛba, ni mɛni ebaafee agbɛnɛ?
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neutral
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kajɛŋgɛ lɛgɛrɛ ŋga màa pye pe kan, pe sila nawa to ki na,
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neutral
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kaw lupe yeaa ,,
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neutral
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Ama n baa' nɛn bo nɛ ki lá tu' uyo wuu nɔ.
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neutral
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nɛ mi ho wáa--,
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neutral
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mbele pè wɛlɛgɛ pe yɛn na gbele na sagawa jaa;
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neutral
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Bhak taa s t waa m par yu paa sa te
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fear
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Ye wele, na tunmbyeele pe yaa kaa yɔgɔri,
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sadness
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O ma nyɛ maa fia gbi ko kɛ wo mi nɛ o hyɛ kaa e piɛɛ he lo.
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anger
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Mboro ŋa maa Yɛnŋɛlɛ sɛnrɛ ti yuun ma yo paga kaa yuun,
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sadness
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Anɛ o le níhi nɛ o ma nyɛ maa pee kɛ tsɔɔ kaa o toɔ o tsui si lo?
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neutral
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Nɛ na munaa pɛrɛ fɔ suumɔ lɔhɔ ni.
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neutral
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E ma ha nɛ wa maa na kaa Mawu susuɔ adesahi a he wawɛɛ.
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fear
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Baa mi Mɛlɛka piŋi puaa diikaŋaa yaa wa haa o yiŋnde bɛndeŋ niŋ?
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anger
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"i love you too kuya ko. mwaaahhh"
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joy
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na fyɔnwɔ fɛnnɛ pe tege,
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fear
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tyoo ndyaa na saa Leina.
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neutral
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Ye bua jɔ wawɛɛ nitsɛ." - Karen.
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neutral
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yaa lumayan
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neutral
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Abonsam ma nɔ mi akɛ kɛji adesai bo lɛ toi lɛ, nibii baaya lɛ jogbaŋŋ aha amɛ.
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fear
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I kii tɔgɛ kee yɛɛ,
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neutral
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Mɛni wa ma nyɛ maa pee konɛ wa ná hemi kɛ yemi nɛ mi wa ngɛ Mawu si womi ɔmɛ a mi?
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fear
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Kyaaa my NC..
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neutral
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ma suu yɛɛ pye fɔ:
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neutral
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Ndɛɛ ki pye Yawe Yɛnŋɛlɛ li sila pye we ni,
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sadness
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Yawe Yɛnŋɛlɛ lii naŋgbanwa sɛnrɛ yo leele mbele na,
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joy
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Yɛ Mose Mla lɛ mli lɛ, abuɔ amɛ akɛ loo ni he tse ni abaanyɛ aye.
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neutral
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Bakɔɔm lɔkɔɔn ballɛ gold wa ulenɛ bɔfɛɛn bwa bubɛpɛnɛ.
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anger
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E kɛ we nɛ nihi fuu ba lejɛ ɔ.
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anger
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Mɛni he je nɛ o susu kaa Mawu dloo mo ɔ, nɛ mɛni he je nɛ o ma nyɛ ma kpa ngmlaa ke 'Nyɛ je Yah yi!' ɔ?
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neutral
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Ni hulu lɛ wa edamɔ shi.
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disgust
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B: N tɛ taa yɔrɔ si.
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sadness
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je vous ai vu (I saw you)
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neutral
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Yaayaa, ɛtɛ sɛn? on Vimeo
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neutral
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ma suu tɛgɛ fyɔngɔ ni Yɛnŋɛlɛ yɛgɛ na."
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fear
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Mɛni ji ní etɛ komɛ nɛ maa ye bua wɔ konɛ wa munyu tumi nɛ wo nihi he wami?
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neutral
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Mɛi ni hi shi yɛ Noa gbii lɛ amli lɛ ateŋ mɛi babaoo fee nibii fɔji.
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neutral
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yaaa... que wena
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neutral
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Benɛ a kpata Egipt ta buli ɔmɛ a hɛ mi ngɛ Wo Tsu ɔ mi ɔ, anɛ Farao yi ná wami lo?
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anger
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Pe yaa ka leele mbele wì wɔ pe gbogolo pe yɛɛ na,
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neutral
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na wɔnlɔŋgbaala pè fɛgɛ na na.
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neutral
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Wvú se nu ɛ la, ɛ kase ɛ yenɛ.'
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neutral
|
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Kabiye Emotion Analysis Corpus
Dataset Description
This dataset contains emotion-labeled text data in Kabiye 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: 22,804
- Joy: 1332 (5.8%)
- Sadness: 928 (4.1%)
- Anger: 895 (3.9%)
- Fear: 773 (3.4%)
- Surprise: 937 (4.1%)
- Disgust: 1368 (6.0%)
- Neutral: 16571 (72.7%)
Dataset Structure
Data Fields
- Text Column: Contains the original text in Kabiye
- 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/kabiye-emotions-corpus")
# Access the data
print(dataset['train'][0])
Citation
If you use this dataset in your research, please cite:
@dataset{kabiye_emotions_corpus,
title={Kabiye Emotions Corpus},
author={Mich-Seth Owusu},
year={2025},
url={https://huggingface.co/datasets/michsethowusu/kabiye-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
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Size of downloaded dataset files:
1.02 MB
Size of the auto-converted Parquet files:
1.02 MB
Number of rows:
22,804