SpecAugment ngir xamme kàddu

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

1. Lu SpecAugment di doxalee?
   • Spektrogram log-mel bi
   • Formu onde audio bu ñor
   • Transkripsioŋ bi
   • Diisaayu model bi
2. Ci ñatti liggéey yi SpecAugment def, ban ci ñoom mooy?
   • soppi ton
   • maskeer fréquence
   • Wecci baat
   • Pikir echo
3. What role did the SpecAugment paper assign to its feature transformations?
   • They guarantee that every recognizer avoids overfitting
   • They replace the need for transcribed training data
   • They augment ASR training inputs and were evaluated for recognition performance
   • They improve every speech model by the same amount
4. Luy 'masking temps'?
   • Dafay efaase timbre yiñ bind
   • Gaawaayal déglu audio bi
   • Dindi noppalu ci ndoorte li
   • Blanks ab span ci jéego yu toppalante
5. How are time- and frequency-mask locations chosen during SpecAugment training?
   • They are randomly sampled, so the same input may receive different masked regions on later passes
   • They are fixed permanently before the training set is collected
   • They are chosen by a language model after each recognition result
   • They are identical for every utterance and every training step
6. Ci ban référence la SpecAugment gëna jàppale ci am resultaa yi gëna xarañ?
   • Nataal Net
   • Kaddu Libri
   • SQUAD
   • KOL
7. What does time warping do in the original SpecAugment policy?
   • It replaces speech frames with translated text
   • It masks every frequency channel permanently
   • It deforms feature positions along the time axis
   • It changes the speaker identity in the waveform
8. Which recognizer architecture did the original SpecAugment paper use in its experiments?
   • A region-based image detector
   • A music source-separation U-Net only
   • A text-only masked language model
   • Listen, Attend and Spell (LAS)