Datasets:

voice-biomarkers
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openslr-32-hq-SA-languages-Sesotho

audio audioduration (s) 1.62 18.4	transcription stringlengths 10 153
	I think it's much nicer to quarrel.
	Maobanyana mona ha a ithimola o ile a butswella mosebetsi wa rona wa sekolo hole kwana.
	Kamora moo tekesi ya hlahella hukung.
	A cry of joy burst from Philip's lips.
	ninety-five one zero
	Joan looked triumphantly at Sheldon, who bowed.
	Red-Eye never committed a more outrageous deed.
	From my earliest recollection my sleep was a period of terror.
	Tshebeletso ya boemo ba lehodimo e noha hore pula e tla na porofinsing ya Leboya.
	Newcastle United e bapetse ka ho lekana le Manchester United.
	Ntja ena eya kwata haholo.
	Nkgono a theoha mme Thoko a arolelana diphepamente tsa hae le Jake.
	Ke kahoo Motjhalla a ileng a fetoha mankgane.
	Ba fihla motlotlwaneng, moo Imbudu ya sutumeletsa Nonkungu morao.
	Philip began to feel that he had foolishly overestimated his strength.
	Ntate wa ka o reketse Rantsipe dikgalase tsa mahlong tse qabolang.
	I obeyed, and a minute or two later they stood before him.
	Anything unusual or abnormal was sufficient to send a fellow to Molokai.
	I have been doubly baptized.
	Ee, nka kgona ha nka ka qhomaqhoma makgetlo a 12.
	He was just bursting with joy, joy over what.
	But here amongst ourselves let us speak out.
	seventy-eight forty-six fifty-two
	Sometimes her dreams were filled with visions.
	Anyway, no one saw her like that.
	Letsatsing le hlahlamang di ne di maketse.
	one ninety-three zero
	A bea kgoho e nonneng hodima botlolo ya jeme eo a e rwetseng hloohong.
	hundred and, thousand and, million and, billion and, trillion and
	A mathela ka tlung ho ya apara, empa a lebala ho kwala fensetere ya kamore.
	Ho bjabjaretsa ke ho etsang?
	What I saw I could not at first believe.
	Ketti a sheba hosele kapele, mme ka matsoho a thothomelang, a qala ho bapala piano ya monwana.
	Labohlano haesale e le letsatsi le leholo la dikgau tsa dinaledi.
	Dikgwedi tse 3 le matsatsi a 12!
	Yaba ka mantswe ana, o hula MaShange o mo isa kgotla ho ya bona Moahlodi Ngwenya.
	Makoloi a hapjwa ka sheshe.
	A tsamaya a ya ho lebokoso la hae, a bula sekwaelo, a neha Kunupi ditshomo kaofela.
	To her the bridge was tambo, which is the native for taboo.
	Swansea City e bapetse ka ho lekana le Manchester United.
	Lenama le kang wena tjee?
	Author of the danger trail, Philip Steels, etc.
	five zero three
	Yaba ka bonngwe, di tswa lepatsong le leboteng moo di neng di dula teng.
	ninety-two two twenty-nine
	Aston Villa e bapetse ka ho lekana le Manchester United.
	Tshepe ya monyako ya re Kete-kete-kete.
	Dinaledi tsa kgauta di tswa pele!
	Sharifa o monyane haholo ho ka utlwisisa se lokileng.
	Bra Tsotsi a tshoha haholo hoo a ileng a kgangwa ke moro wa peri-peri, mme a kgitlwa ke thabi.
	The lines were now very taut.
	Metsi a metsi haholo.
	Diphoofolo tsohle tsa phahamisa dihlooho tsa sheba mme tsa qala ho mathela nokeng.
	A half a case of tobacco was worth three pounds.
	Nkgo ya re bjara.
	Ka tsatsi le leng Lwazi a fumana setulo sa kgale se sututswang thoteng e haufi le habo.
	Tloha mona, Domino!
	Ke tla kopana le wena hekeng ena hosane, hang ha letsatsi le qeta ho tjhaba.
	Mohudi ke o matla Rustenburg, mme dikgato ke tse 23.
	Hobaneng ha o rata ho sebetsa mona?
	Black Aces e hlotse Chelsea ka dintlha tse 4 ho tse 3, nakong ya ho raha dipenele.
	Ke dikgato tse 25 le sefefo sa moya mona Durban
	Here the explosion of mirth drowned him out.
	zero three nine
	Platinum Stars e hlotswe ke Chippa United ka dintlha tse 7 ho tse 3, papading ya PSL.
	Juventus e bapetse ka ho lekana le Chelsea.
	Mandela o dula hokae?
	But a strange thing happened.
	Ke mang eo e neng e le molaodi wa provense ya Kwazulu-Natala?
	Ke dikgato tse 19 mme ho maru ka ho kgetha dibaka mona Johannesburg
	Kgwedi e fetileng, e ne e le e maphatephate sebakeng sa tlhokomelo ya diphoofolo.
	Not at this particular case, Tom, apologized Whittemore.
	Mamelodi Sundowns e bapetse ka ho lekana le SuperSport United.
	Imbudu e ile ya ya harangwane Mtonyama yare Ke motjhana wa hao, Nonkungu.
	Jomo Cosmos e bapala le Liverpool ka Labone ka phirimana, setadiamong sa Themba Senamela.
	And you always want to see it in the superlative degree.
	Get down and dig in.
	Leba North-West ka seterata sa Albertyn, ebe o thinyetsa ka ho le letshehadi.
	Will we ever forget it.
	Bakeng sa mosebetsi ona o ile a lefshwa ka dikhoine tse mmalwa tsa silefera.
	If you mean to insinuate -- Brentwood began hotly.
	For an instant he saw Pierre drawn like a silhouette against the sky.
	eight three one
	Ho hapjwa ke tse tumileng.
	Tsatsing le hlahlamang hoseng Sisanda a tsoha a ena le mohopolo o itseng!
	zero forty-two eleven
	He had comparatively no advantages at first.
	Ke dikgato tse 21 mme letsatsi le tjhabile mona Hermanus
	Bakeng sa mosebetsi ona o ile a lefshwa ka dikhoine tse mmalwa tsa silefera.
	The sharp voice of Wolf Larsen aroused me.
	Dinku di ne di tshohile haholo hoo di ileng tsa baleha kaofela.
	When I came to I was waving my hat and murmuring ecstatically.
	thirty-two zero one
	Then, and at supper, he tried to fathom her.
	I had faith in them.
	Kgato e 1 ka tlase ho 0, Humansdorp, ka pula ya sefefo le sefako.
	Ke dikgato tse 12 mme ho na le mafafatsane mona Cape Town
	Sethibathibane sa Bafana Bafana, George Lebese o kgonne ho thiba bolo makgetlo a 5 e se e le mokwallong, nakong ya papadi.
	Makoloi a hapjwa ka sheshe.
	Ho fihlela lena le hodimo, dipela di na le mehatla e mekgutshwane e bokopa, jwaloka Haruki!

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High quality TTS data for four South African languages - Sesotho

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

Identifier: SLR32

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

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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