UMHLAHLANDLELA WE-AI womsindo

I-WaveNet

I-WaveNet, eyethulwe ngabakwa-DeepMind ngo-2016, bekuyinethiwekhi ye-neural ephumelelayo ekhiqiza umsindo ongahluziwe isampula eyodwa ngesikhathi, ekhiqiza inkulumo yemvelo emangalisayo nomculo.

Uhlolojikelele

I-WaveNet, eyethulwe ngabakwa-DeepMind ngo-2016, bekuyinethiwekhi ye-neural ephumelelayo ekhiqiza umsindo ongahluziwe isampula eyodwa ngesikhathi, ekhiqiza inkulumo yemvelo emangalisayo nomculo. Isethe izinga lesimanje lokuthembeka okuphezulu kombhalo-kuya-enkulumweni.

I-WaveNet ihlezi ku-audio-AI workflows eguqula inkulumo, umculo, nomsindo wokuxhumana, ukufinyeleleka, nokukhiqizwa kwemidiya.

I-Deep Dive

I-WaveNet iyimodeli ekhiqizayo ezenzakalelayo: ibikezela isampula ngayinye yomsindo ebekwe kuwo wonke amasampuli angaphambi kwayo, ngokuvamile kumasampuli angu-16,000 noma angu-24,000 ngomzuzwana. Ukuqanjwa kwayo okuyisisekelo kuyinqwaba ye-convolutions enwetshiwe ye-causal. I-Causal isho ukuthi imodeli ibheka emuva kuphela ngesikhathi, igcina ukuhleleka kwesizukulwane; ukunwetshwa kusho ukuthi isendlalelo ngasinye seqa inani elikhulayo lamasampuli, ngakho isitaki esinesizotha simboza izinkulungwane zamasampuli (inkambu ebanzi eyamukelayo) ngaphandle kwezindleko ezinkulu. Isekelwe ezicini zolimi noma i-mel-spectrogram, i-WaveNet ikhiqiza inkulumo eyimvelo kakhulu kunamavokhoda e-concatenative kanye ne-parametric ayandulele, evala isikhala esikhulu ekurekhodweni kwabantu futhi inika amandla izinguqulo zangaphambili zomsizi Google.

I-Technical Insight

I-convolutions enwetshiwe iyiqhinga elibalulekile: ngamanani okunwebeka angu-1, 2, 4, 8, njalo njalo, inethiwekhi kuphela amashumi ezendlalelo ezijulile ezingabheka izinkulungwane zamasampuli adlule, ithwebula yomibili imininingwane emihle ye-waveform kanye nesakhiwo eside se-prosodic. Okuphumayo kumodeli yevelu yesampula ngayinye njengokusatshalaliswa kwezigaba (ekuqaleni amaleveli angu-256 ngokuhlanganisa i-mu-law), kanye namayunithi okuqalisa afakwe esangweni kanye nezinsalela nokuxhumeka kokweqa kusimamisa ukuqeqeshwa kwalesi sitaki esijule kakhulu.

Ukushintshanisa okungcono kakhulu kwe- WaveNet

I-WaveNet, eyethulwe ngabakwa-DeepMind ngo-2016, bekuyinethiwekhi ye-neural ephumelelayo ekhiqiza umsindo ongahluziwe isampula eyodwa ngesikhathi, ekhiqiza inkulumo yemvelo emangalisayo nomculo. Isethe izinga lesimanje lokuthembeka okuphezulu kombhalo-kuya-enkulumweni. I-WaveNet ihlezi ku-audio-AI workflows eguqula inkulumo, umculo, nomsindo wokuxhumana, ukufinyeleleka, nokukhiqizwa kwemidiya. Ukuze wakhe ukuqonda okujulile, phatha i-WaveNet njengemodeli yokusebenza, hhayi isici esisodwa: chaza imiphumela oyifunayo, ucacise ukucabanga, futhi uhlukanise lokho uhlelo olungakwenza ngokwethembeka kulokho okusadinga ukwahlulela kochwepheshe.

Empeleni, amaqembu aqinile asebenzisa i-WaveNet aphatha ikhwalithi, ukubambezeleka, kanye nemvume njengezingxenye ezibaluleke ngokulinganayo zesu lokuthunyelwa. Babhala imibandela yempumelelo ecacile, ukuhlola okuqhathaniswa nedatha engokoqobo nokugeleza komsebenzi, futhi baphindaphinde ngokusekelwe kumaphethini okuhluleka aqashiwe esikhundleni sokuwina kwebhentshimakhi yesikhathi esisodwa. Yilapho ukuqonda kwethiyori kuguquka kube amandla ahlala njalo kuwo wonke umkhiqizo, inqubomgomo, kanye nokusebenza.

Ithuthukisa ukufinyeleleka ngokuloba, ukulandisa, nezixhumi ezibonakalayo zezwi. Ngesikhathi esifanayo, ukusetshenziswa kabi kwezwi kanye nezingozi zokuzenza ongeyena ziyakhuphuka uma imvume ingekho. Indlela eqine kakhulu iwukuhlanganisa isivinini sokuhlola nesiyalo sokuphatha: qhuba abashayeli bezindiza, bamba ubufakazi, ushicilele amalogi ezinqumo, futhi ubuyekeze izivikelo ngokuqhubekayo njengoba imodeli yokuziphatha, okulindelwe ngabasebenzisi, kanye nezimfuneko zokulawula zishintsha.

I-Strategic Impact

Ithuthukisa ukufinyeleleka ngokuloba, ukulandisa, nezixhumi ezibonakalayo zezwi.

Ithuthukisa ukufinyeleleka ngokuloba, ukulandisa, nezixhumi ezibonakalayo zezwi. Ekusetshenzisweni kwekhwalithi ephezulu, lokhu kuhunyushwa emithethweni yokusebenza elinganisekayo, imingcele yobunikazi, nemikhuba yokubuyekeza ephindelelayo ukuze amaqembu akwazi ukukala ukuzethemba esikhundleni sokukala ukungaqondakali.

Amaqembu emidiya angathumela umsindo opholishiwe ngokushesha ngamabhajethi amancane.

Amaqembu emidiya angathumela umsindo opholishiwe ngokushesha ngamabhajethi amancane. Ekusetshenzisweni kwekhwalithi ephezulu, lokhu kuhunyushwa emithethweni yokusebenza elinganisekayo, imingcele yobunikazi, nemikhuba yokubuyekeza ephindelelayo ukuze amaqembu akwazi ukukala ukuzethemba esikhundleni sokukala ukungaqondakali.

Amasistimu abhekene nekhasimende angacubungula ukusebenzelana okukhulunyiwe ngesilinganiso esikhulu.

Amasistimu abhekene nekhasimende angacubungula ukusebenzelana okukhulunyiwe ngesilinganiso esikhulu. Ekusetshenzisweni kwekhwalithi ephezulu, lokhu kuhunyushwa emithethweni yokusebenza elinganisekayo, imingcele yobunikazi, nemikhuba yokubuyekeza ephindelelayo ukuze amaqembu akwazi ukukala ukuzethemba esikhundleni sokukala ukungaqondakali.

Ikusasa le-WaveNet

I-WaveNet yoqobo ibihamba kancane ngoba ukusampula kuyalandelana. Abalandelayo balungise lokhu: I-Parallel WaveNet ne-WaveRNN inike amandla ukuhlanganiswa kwesikhathi sangempela, futhi kamuva ama-vocodes asuselwa ku-flow- kanye nasekelwe ku-GAN njenge-WaveGlow ne-HiFi-GAN, kanye namavokhoda okusabalalisa, aphushe ikhwalithi nesivinini ngokuqhubekayo. Imibono ye-WaveNet ye-autoregressive, ne-dilated-convolution iphila kulezi zinhlelo futhi ibe nomthelela wezakhiwo ezingaphezu komsindo, iqinisa ifa layo ekumodeleni okukhiqizayo.

Ukuqaliswa Komhlaba Wangempela

Ikhiqiza amazwi azwakalayo emvelo Google Umsizi kanye Google Umbhalo-kuya-Inkulumo Yamafu

Isebenza njenge-neural vocoder eshintsha i-mel-spectrogram ibe ama-waveform kumapayipi e-TTS afana ne-Tacotron 2

Ihlanganisa upiyano wangempela nomculo wezinsimbi ovela kumsindo ongahluziwe

Ukuhlanganiswa kwezwi kwamathuluzi okufinyelela nokulandisa kwe-audiobook

Amaphethini Okusebenzisa

I-WaveNet isebenza

Ikhiqiza amazwi azwakalayo emvelo Google Umsizi kanye ne-Google Umbhalo-kuya-Inkulumo Yamafu.

Ukukhiqiza amazwi azwakalayo emvelo Google Umsizi kanye Google Amathimba Amafu Wombhalo-ube-Inkulumo ngokuvamile athola imiphumela engcono uma echaza izilinganiso zekhwalithi ngaphambili, agcina indlela yokukhuphuka komuntu ezimweni ezibucayi, futhi alandelele kokubili izinzuzo zokukhiqiza nezindleko zamaphutha ngokuhamba kwesikhathi.

I-WaveNet isebenza

Isebenza njenge-neural vocoder eshintsha i-mel-spectrograms ibe ama-waveform kumapayipi e-TTS afana ne-Tacotron 2.

Isebenza njenge-neural vocoder eshintsha ama-mel-spectrogram abe ama-waveform kumapayipi e-TTS afana namaThimba e-Tacotron 2 ngokuvamile athola imiphumela engcono lapho echaza imingcele yekhwalithi ngaphambili, egcina indlela yokukhuphuka yomuntu yamacala asemaphethelweni, futhi alandelele kokubili izinzuzo zokukhiqiza nezindleko zamaphutha ngokuhamba kwesikhathi.

I-WaveNet isebenza

Ihlanganisa upiyano wangempela nomculo wezinsimbi ovela kumsindo ongahluziwe.

Ukuhlanganiswa kwepiyano engokoqobo nomculo wezinsimbi ovela emaQenjini omsindo ongahluziwe kuvame ukuthola imiphumela engcono uma echaza izinga eliphezulu ngaphambili, agcine indlela yokukhuphuka yomuntu yamakesi asemaphethelweni, futhi alandelele kokubili izinzuzo zokukhiqiza nezindleko zamaphutha ngokuhamba kwesikhathi.

I-WaveNet isebenza

Ukuhlanganiswa kwezwi kwamathuluzi okufinyelela nokulandisa kwe-audiobook.

Ukuhlanganiswa kwezwi kwamathuluzi okufinyeleleka kanye namathimba okulandisa kwe-audiobook ngokuvamile athola imiphumela engcono uma echaza izilinganiso zekhwalithi ngaphambili, agcine indlela yokukhuphuka yomuntu yamakesi asemaphethelweni, futhi alandelele kokubili izinzuzo zokukhiqiza nezindleko zamaphutha ngokuhamba kwesikhathi.

Izingozi & Guardrails

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Ukusetshenziswa kabi kwezwi kanye nezingozi zokuzenza ongeyena ziyanda uma imvume ingekho.

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Ukunemba kungase kwehle kuzo zonke izinhlobo zokuphimisela, izilimi zesigodi, noma izindawo ezinomsindo.

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Umsindo wokwenziwa ungenziwa iphutha njengenkulumo eyiqiniso ngaphandle kokulebula okucacile.

Ukuqalisa Umhlahlandlela

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Thola imvume esobala yokuthwebula izwi, ukuhlanganisa, nokusebenzisa kabusha.

Thola imvume esobala yokuthwebula izwi, ukuhlanganisa, nokusebenzisa kabusha. Phatha isinyathelo ngasinye njengesango lobufakazi: uma imibandela ingafinyelelwa, misa ukukhishwa, vala igebe, bese unweba ukusetshenziswa.

2

Ikhwalithi yokuhlola kuzo zonke izipikha nezimo zangemuva.

Ikhwalithi yokuhlola kuzo zonke izipikha nezimo zangemuva. Phatha isinyathelo ngasinye njengesango lobufakazi: uma imibandela ingafinyelelwa, misa ukukhishwa, vala igebe, bese unweba ukusetshenziswa.

3

Chaza ukuthi kunini lapho umuntu kufanele abuyekeze noma agunyaze okuphumayo.

Chaza ukuthi kunini lapho umuntu kufanele abuyekeze noma agunyaze okuphumayo. Phatha isinyathelo ngasinye njengesango lobufakazi: uma imibandela ingafinyelelwa, misa ukukhishwa, vala igebe, bese unweba ukusetshenziswa.

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Lebula umsindo wokwenziwa futhi ugcine amarekhodi atholakalayo ukuze aziphendulele.

Lebula umsindo wokwenziwa futhi ugcine amarekhodi atholakalayo ukuze aziphendulele. Phatha isinyathelo ngasinye njengesango lobufakazi: uma imibandela ingafinyelelwa, misa ukukhishwa, vala igebe, bese unweba ukusetshenziswa.

Qhubeka Uhlole