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