VITS Dhammaadka-ilaa-Dhamaadka Kediska Hadalka

Jawaabaha iyo sharraxaadaha waxay soo baxayaan markaad qaadanayso kediska.

1. Muxuu u taagan yahay erayga gaabin VITS?
   • Farqiga kala duwan ee barashada iska hor imaadka ee dhamaadka-ilaa-dhamaadka Qoraal-ilaa-hadal
   • Nidaamka Beddelka Codka Farshaxanka
   • Soosaaraha-Taxanaha-Waqtiga-isku-dhafan ee Vocoder-ka
   • Soo Gelitaanka Muuqaal ee Qoraallada
2. Waa maxay farqiga ugu weyn ee qaab dhismeedka u dhexeeya VITS iyo dhuumaha dhaqameed ee TTS?
   • VITS waxay isticmaashaa laba marxaladood oo si gaar ah loo tababaray
   • VITS waxay si wadajir ah u tababbaraan qaabka codadka iyo cod-bixiyaha, iyagoo si toos ah uga socda qoraalka una socda qaab hirarka
   • VITS waxa ay u baahantahay mudoyinka telefoonka gacanta lagu calaamadeeyay
   • VITS kaliya waxay soo saartaa mel-spectrograms
3. Sidee VITS u bartaa isku toosinta u dhaxaysa qoraalada iyo sawirada maqalka?
   • Isku toosiye qasab ah oo dibadda ah oo horay loo tababaray
   • Tilmaamaha gacanta ee aqoonyahannada afafka
   • Raadinta Is-waafajinta monotonic (MAS) inta lagu jiro tababarka
   • Meelayn aan toos ahayn oo lagu safeeyey xoojinta barashada
4. Waa maxay sababta VITS ay ugu jirto saadaasha muddada stochastic?
   • In odhaah kasta laga dhigo mid isku mid ah oo joogto ah
   • Si loo cadaadiyo cabbirka faylka maqalka ah
   • Si aad qoraalka ugu tarjunto luqado kale
   • Si loo soo saaro qaafiyado hadalka dabiiciga ah oo kala duwan isla qoraalka
5. Qaybtee ayaa ku riixaysa wax-soo-saarka VITS xagga maqalka dhawaaqa dhabta ah?
   • Takoorka qaabka GAN oo isticmaalaya tababar iska soo horjeeda
   • Qaabka abaalmarinta barashada xoojinta
   • Shaandheeyaha hab-socodka signal-ku-salaysan ee qaanuunka
   • Module-hubi higgaad
6. Which cited system explicitly builds on VITS for zero-shot multispeaker and multilingual synthesis?
   • FastSpeech 2
   • YourTTS
   • WaveNet
   • A deterministic vocoder with no speaker conditioning
7. What does the normalizing-flow component contribute to VITS?
   • It replaces text-audio alignment with a speaker identity check
   • It guarantees identical duration for every spoken phrase
   • It increases the expressiveness of the latent prior distribution
   • It removes the waveform decoder from the model
8. Why does VITS use both variational inference and adversarial learning?
   • They make the model independent of text input
   • They guarantee every generated voice is a real speaker
   • They remove all duration variation
   • They support latent-variable modeling and realistic waveform generation