Datasets:

voice-biomarkers
/

openslr-32-hq-SA-languages-isiXhosa

audio audioduration (s) 1.1 17.5	transcription stringlengths 7 165
	Enye intlanzi imke negwegwe lam.
	EReddersburg amaqondo obushushu aziidigrizi ezi-25 kukho nomoya ovuthuza ngamandla.
	Akazange abaxelele ngephupho lakhe elenza ukuthi amayizele entliziyweni yakhe.
	Hawu, hawu, akusemnandi, wakhonkotha uDomino, etsiba ephuma phantsi kwebhedi.
	Ingqikelelo ibonisa iimpawu zee-*project zedijithali, isandi esintywiliselayo kunye nezihlalo ezicambalalayo.
	Kutheni upeyinte ulwandle?
	four zero seven
	Warhotyoza egoduka eqaqanjelwa esabanjwe linxele likakhetsekile Wayekhethazeke kakhulu uDyakalashe.
	sixty-eight thirty-four ten
	Every bone in her aged body seemed broken or dislocated.
	Gqibani iblakfesi yenu, bantwana, uMakhulu utshilo.
	trillion and, billion and, million and, thousand and, hundred and
	Yet he dreams he is immortal, I argue feebly.
	UMvundla unamendu adlula nawomoya.
	Kodwa amantshontshwana akhe ayengamhoyanga.
	Ngephanyazo, uDell wafikelwa lelona cebo likrelekrele nelimangalisayo.
	Bafikelele njani kwisigqibo?
	KwiPSL, iJomo Cosmos yabetha iUniversity of Pretoria ngamanqaku ayi-9 kwayi-3.
	Ihagu ayifuni kutsiba ecingweni kwaye kuya kusiba mnyama ngoku.
	It fairly clubbed me into recognizing it.
	Baza beva umgqumo.
	For such countries nothing remained but reorganization.
	Ngexesha esethekweni umvundla waye watya, wasela, wade waxhentsa.
	I came for information more out of curiosity than anything else.
	I suppose you wonder why she is coming up here.
	A new preacher and a new doctrine come to Jerusalem.
	Umdlali odlala ephikweni uMusa Nyatama wadlulisa iibhola ezi-11.
	zero forty-two one
	UMagozwe wayephupha ngokuba ngumqhubi weenqwelo-moya.
	Wakroba ekoneni yophahla.
	Umdlali wasesiswini uTshepang Machedi wakhabela iibhola eziyi-11 ezipalini.
	Wonke nje umntu uyagramza, konwatyelwe ukutya okumnandi, usebeze watsho kalusizi.
	Walixhwila elo rherheba le-R100 waza waphela emehlweni kuloo nginginya.
	Kwaye impumlo yam iyaliva ivumba leejalebisi zigcadeka egumbini lokuphekela likamama.
	Death had come with terrible suddenness.
	Kodwa msinyane luyaphola ndiluginye.
	Bala kwakhona.
	zero thirty-four one
	IBloem Celtic neNewcastle United zadlala zombini ngoMgqibelo kwibala lezemidlalo iSoccer City.
	Impilo yakho iyalana neekati, Sibu, kutsho uNkosikazi Magona.
	It lived in perpetual apprehension of that quarter of the compass.
	Ungumhlobo onjani lo ofuna ukutya omnye wabantwana bam?
	UZimkhitha wajonga elo gquba labantu laliyiyizela lihleka limqhwabela izandla.
	Iqela lizichaza njengantoni?
	Ube yindawo yesazulu sombutho okhuthaza idemokhrasi.
	INewcastle United ibethe iJuventus xa kugqityezelwa umdlalo ngeepenalthi ngamanqaku ayi-9 kwayi-5.
	Ndenza umatrayivethi, ucacise njalo uLwazi.
	Amaqondo obushushu eStanderton aziidigrizi Selsiyasi ezi-48.
	Ithathwa njengendlunkulu yabathandani besini esinye e-Afrika.
	Mingaphi iminyaka yakho, tata?
	And Raoul listened again to the tale of the house.
	Iintuku zafuna ukuzigrumbela eyazo imingxuma.
	five four six
	six three one
	UNdlovu weza neemarula eziswiti namandongomane.
	Umshumayeli omtsha nemithetho yecawa eza eJerusalem.
	four eight eight
	Jonga ijezi yakho inoboya obumnyama, watsho uMnumzana Samson esolatha.
	His outstretched arm dropped to his side, and he paused.
	What Pascal glimpsed with the vision of a seer, I have lived.
	UNhlanhla Vilakazi wafumana ikhadi elibomvu kusompempe.
	Yathi ngcu kwisebe lomthi ithatha isiqabu.
	Ubhuti kaWangari waabacenga abazali ukuba bavumele uWangari aye esikolweni.
	Umqeqeshi wafaka uMpho Thulo endaweni kaPhumlani Ntshangase umdlalo usanda kuqala.
	KwiLigi yeBhola yooMpondozihlanjiwe yamaNgesi, iLeicester City yabethwa yiNorwich City ngamanqaku asi-8 kwama-3.
	eight five one
	Xa begula kwakungekho mntu wokubanceda.
	Kakade nje, kwakungekho dyakalashe.
	UTebogo Monyai wakhabela ibhola phambili.
	Hayi ayifani tu!
	UMfene noNkawu bancuma ngolonwabo.
	Thatha u-R21 ukuya e-Kempton Park umgama weekhilomitha ezi-43.
	He bore no grudges and had few enemies.
	EAlice amaqondo obushushu angaphantsi kwedigrizi eyi-1 kukho nenkungu.
	four zero two
	Ukufa kukaSizwe yilahleko enkulu, watsho umfazi womfama wobisi emva komngcwabo.
	UMakhulu waphakamisa amehlo kumthungo wakhe waza uMama wakroba ekoneni.
	thirty-four zero one
	Emva koko yamkrwempa yamluma, wade wanyanzeleka ukuba ayiyeke.
	Uyaphi uhamba wedwa nje?
	Namhlanje lusuku lwemarike, utshilo.
	Amaqondo obushushu aziidigrizi ezi-17 eImpendle kuyakubakho nomoya kusasa.
	Kakade nje, kwakungekho dyakalashe.
	We have plenty of capital ourselves, and yet we want more.
	Sabasa umlilo omkhulu, sagibisela ilitye elinqgukuva elingudileyo emlilweni.
	SIYAYIBONA IPENTI YAKHO, KWAYE INOMGQOBHO!
	What was the object of your little sensation.
	Ekugqibeleni umqhubi weteksi wemisa erenkini.
	Bathi xa befika emlanjeni batshintsha izikhundla uMvundla wabeleka emqolo kuFudo.
	Idyasi yakhe enzima yamtsalela ezantsi warhaxwa.
	Tyhini khangela izityalo.
	Ayikho kwimeko entle kakhulu.
	Ekupheleni kwedlelo kwakukho amawa namatyholo.
	It was his intention to return to Eileen and her father.
	Ndifuna umhlobo endinokuqubha naye andichithise isithukuthezi.
	seventy-five five fifty
	nine two six
	Gregson was asleep when he re-entered the cabin.
	Umdlali odlala ephikweni uKhumbulani Banda wadlulisa iibhola eziyi-4.
	Ingaba iphi ikayiti yam ngoku?

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High quality TTS data for four South African languages - isiXhosa

Source - https://openslr.org/32/

Identifier: SLR32

Summary: Multi-speaker TTS data for four South African languages - isiXhosa

License: Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)

About this resource:

This data set contains multi-speaker high quality transcribed audio data for four languages of South Africa. The data set consists of wave files, and a TSV file transcribing the audio. In each folder, the file line_index.tsv contains a FileID, which in turn contains the UserID and the Transcription of audio in the file. The data set has had some quality checks, but there might still be errors.

This data set was collected by as a collaboration between North West University and Google.

If you use this data in publications, please cite it as follows:

  @inproceedings{van-niekerk-etal-2017,
    title = {{Rapid development of TTS corpora for four South African languages}},
    author = {Daniel van Niekerk and Charl van Heerden and Marelie Davel and Neil Kleynhans and Oddur Kjartansson and Martin Jansche and Linne Ha},
    booktitle = {Proc. Interspeech 2017},
    pages = {2178--2182},
    address = {Stockholm, Sweden},
    month = aug,
    year  = {2017},
    URL   = {http://dx.doi.org/10.21437/Interspeech.2017-1139}
  }

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Size of downloaded dataset files:

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Number of rows:

2,420