Quiz ci arsitektu kàddu yu xóot

Sooy def quiz bi, tontu yi ak leeral yi dañuy feeñ.

1. Ban fonction perte mooy may DeepSpeech mu tàggat te du am niveau de cadre ci digganté audio ak text?
   • Jumtukaay kaare moyen
   • Entropi cross ci kaw palanteer yu am guddaay bu takku
   • Xeetu jamonoy lëkkaloo (CTC)
   • Ñàkk ñatti doom
2. Lan mooy filosofi architecture bi DeepSpeech siiwal?
   • Taggat yaram bu yam ci benn reso neuronal, daale ko ci man-mani audio ba ci bind
   • Séddale xàmmee ci pàcc yu bari yuñ defaree loxo, ñu tàqale
   • Jëfandikoo ay diksoneer fonetik yu lalu ci sàrt
   • Xamme kàddu rek ci méngoo ak template
3. Lu tax DeepSpeech di jëfandikoo ab layer buy dellusi ci ñaari yoon?
   • Ngir wàññi dayo fichier audio bi
   • Jox bépp xam-xam bu lalu ci kaadar yi weesu ak yiy ñëw
   • Tekki ci diggante làkk yi
   • Ngir dindi soxla bépp done tàggat
4. Ban xeetu man-mani dugal la DeepSpeech di faral di doxalee?
   • Done pixel yu ñor
   • Transkripsioŋ yiñ njëkka bind
   • Etiketu metadone MP3 yuñ komprime
   • Spectrogram wala man-mani MFCC yuñ xayma ci kaw kadre audio yu gàtt
5. Lan lañuy faral di yokk ci waxtu dekode ngir gëna baaxal tànneefi baat yi ak ortograafi DeepSpeech?
   • Benn xeetu làkk bu bawoo ci biti (lu melni xeetu n-gram)
   • Ñaareelu mikro
   • Xayma nataal bu gëna mag
   • Puce encryption hardware
6. What does the original DeepSpeech output layer predict at each acoustic time step?
   • A fixed speaker-identity vector only
   • A single complete translated document with no time steps
   • A probability distribution over character labels and the CTC blank
   • The recording's filename and compression format
7. How does CTC relate an acoustic-frame label path to the final DeepSpeech transcript?
   • It sorts all character labels alphabetically
   • It requires exactly one audio frame for each word
   • It keeps every repeated frame label as a separate written character
   • It collapses repetitions and removes blank symbols according to the CTC rule
8. Why does original DeepSpeech's bidirectional acoustic context matter when designing a live recognizer?
   • Bidirectional recurrence needs no future observations
   • Future-frame context requires lookahead or waiting, so it is not automatically zero-lookahead streaming
   • The network can know later audio before it is recorded
   • A character language model removes all buffering requirements