Datasets:

galsenai
/

wolof_tts

audio audioduration (s) 0.74 171	text stringlengths 1 109	gender stringclasses 2 values
	Fan lay sax ?	male
	Saa boo ragalee Yàlla Buur bi moom miiy Kenn, ku dul Yàlla dalay ragal.	male
	Buma ko jàppe.	male
	Ndox mi mu ëmb, cafka gi dafay sëccwex	female
	Tom gisu ko woon.	female
	Ma kay wayal Seex Saalihu.	male
	03/07 à 2330 Mine Ubbi njël lu njëkk li	female
	Mas naa jaay lii.	female
	Damaa yeex a ñëw.	female
	manees na am yaakaar ci moom.	female
	Jën dax na, tay .	male
	Kuy seenub jkat?	male
	Fi mu am	male
	Buy délsi yal na nu fekk ak may gu suuxali may	female
	Maa ngi tëddoon sama lal.	male
	Sama liggéey dafa géey.	female
	Bul bàyyi !	male
	Toma ngi ci kaw.	female
	Biirmaani ci lu bari Bëj-saalum-penku Asi la ñu koy boole.	female
	Xawma woon ne aw fen la.	male
	Bëggu ñu la.	male
	Damaa bëggoon a doon ndaw.	male
	Wax naa dëgg, am déet ?	female
	Soxla naa ab farandoo.	female
	dinaa leen gindi	female
	Ñu ngi ko tëye ca màkkaanum mu mag mu alkaati ya ca Ndakaaru.	female
	Buleen ma xaar.	female
	Bàyyi ma ma nelaw.	female
	Jaxaay ji ak picc mi	female
	Maa ngi jéggalu	female
	Danuy jënd ay CD.	female
	Suuf si daa di nangu.	female
	Du sama mbir.	female
	Xale yi gëmewuñu ko woon	female
	Mbooram bi dëgg la.	female
	Ci mbirum doomu weñ yi jigéenu-wérul war a wann	male
	Loo soxla ?	male
	Bàyyee gu Otris bàyyee Itaali Venezia.	male
	Loolu, du lu ma jékki-jekki rekk def ko	male
	Ay nit lañu.	male
	Bëgg naa ci benn !	female
	Nos dooley kaaraange ji	male
	Doon naa ko ñaawal.	female
	Nekkon na nu ay xarit.	male
	Daa jubb lool.	male
	Da koo kott.	male
	Dangaa ñàkk jafe-jafe lool.	male
	sunuy jafe-jafe ci wàllu paj soppikuwul.	female
	Jëfandikoo ko walla nga ñàkk ko.	male
	Dama xalaat ne danga reelu.	female
	Bunu wuute nag, foofu la liggéey bi nekk	male
	Damaa am ñaan.	female
	Setalal sa néeg bi !	male
	Toogal fii ak nun.	male
	Taariix	male
	Moos mi xossi nama.	male
	Naj ak forse	female
	Danga may fen ?	female
	Noo rëyee nii?!	female
	Nu ngi nekkandoowaat.	female
	Teew fa nag, doore ko ci sawaal digg-bëccëg ba jant so	female
	Dafa dégg i coow.	female
	Mbir mii daal, kenn setu ci.	female
	Am na ci ñent yoy ñi ngi ame ca armal ga	male
	Tur wi feeñ na ci Injiil ci Mk 317.	male
	waaye ak bii yamale, dëgërluwiin gi dafay aju ci tàngaayu wërlaay gi mu ne	female
	Mbaa kuy rambaaj naankat bu màndi xaaloo	male
	Mu ne «Ñoom de ñook woor diirub jamonoo yam».	female
	Masuma faa dellu.	female
	Beto De Canda	female
	Tom sopp na mool yi.	female
	Ma defoon ko ngir moom.	male
	Daanaka, demewu fa noonu	female
	mu wàcc-liggéey Sëriñ Abdu Laat Mbàkke wuutu ko di xalifab Sëriñ Tuubaa.	female
	Damaa bëgg aar.	female
	Wéer ngànnaay gi nag lii la wax	female
	Moom la leen	male
	Melal ni yaay man.	male
	Ndax jekk ngeen ?	male
	Man ngaa lakk farañse a?	female
	Jox naa la ko am ?	male
	Dañu maa féexal.	female
	Booyal bay ab tool booyal ko am at door koo bayaat	female
	Babilon dëkku penku la woon, di péeyug réewu Kalde, maanaam Irak	female
	Tus-wu-taxaw wenn la ci ñaari xammikaay yi beneen bi mooy tus-wu-gaar	female
	Yokkal tuuti meew.	male
	Mooy ne, bala dara, Séex Anta tekkikat la woon	female
	Jéem naa lépp.	male
	defleen ag tànn !	male
	Boo seetloo, sunu way-tawati Covid-19 yu jëkk yi bitim-réew lañ jóge	female
	Man nanu koo am it jaare ko ci yeneen i lijjanti.	female
	XEESAL WALLA XEEB SA BOPP ?	female
	Waxi Seex Anta Joob ju aju làkkSoppi	female
	Damaa sonn lool?!	female
	Àdduna wori neen la.	female
	Lii sax caaxaan lay niru	male
	Loo leen di nëbb ?	female
	Yeneen waat yi it noonu lañu mel.	female
	Ku wax ?	male
	Dina soxla itam ab sàkket leeg-leeg ngir mu man a law ci kawam	male

End of preview. Expand in Dataset Viewer.

Wolof TTS

Dataset Description

This is a Wolof Text To Speech (TTS) dataset collected by Baamtu Datamation as part of the AI4D African language program. The original dataset is hosted on Zenodo and it contains recordings from two (02) natif Wolof speakers (a male and female voice). Each speaker recored more than 20,000 sentences.

Speaking time:

-- Male: 22h 28mn 41s
-- Female: 18h 47mn 19s

The text dataset comes from news websites, Wikipedia and self curated text.

Citation

You can access the project paper at https://arxiv.org/abs/2104.02516.
If you work on the dataset, please cite the authors below.

@dataset{thierno_ibrahima_diop_2021_4498861,
  author       = {Thierno Ibrahima Diop and
                  Demba AW and
                  Ami jaane and
                  Mamadou Badiane},
  title        = {WOLOF TTS(Text To Speech) Data},
  month        = feb,
  year         = 2021,
  publisher    = {Zenodo},
  version      = 1,
  doi          = {10.5281/zenodo.4498861},
  url          = {https://doi.org/10.5281/zenodo.4498861}
}

This dataset was made available on HuggingFace through GalsenAI's mission to strengthen Senegal's AI ecosystem. It was cleaned and structured by Derguene Mbaye, then uploaded and documented by Alwaly Ndiaye.

Downloads last month: 206

Size of downloaded dataset files:

4.57 GB

Size of the auto-converted Parquet files:

4.57 GB

Number of rows:

40,010

Models trained or fine-tuned on galsenai/wolof_tts

dofbi/wolof-asr

Audio-Text-to-Text • Updated 25 days ago • 129