SpecAugment ee Kediska Aqoonsiga Hadalka

Jawaabaha iyo sharraxaadaha waxay soo baxayaan markaad qaadanayso kediska.

1. Muxuu ku shaqeeyaa SpecAugment?
   • spectrogram-ka log-mel
   • Qaabka hirarka codka ceeriin
   • Qoraalka qoraalka
   • Miisaanka qaabka
2. Midkee ka mid ah kuwan saddexda hawlgal ee SpecAugment?
   • rogaal celinta
   • Maaskaro soo noqnoqda
   • Beddelka ereyga
   • Echo cirbadeynta
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. Maxay qabtaa 'time masking'?
   • Tirtiraa qoraalada wakhtiyada
   • Waxay kordhisaa dib-u-ciyaarista maqalka
   • Waxay ka saartaa aamusnaanta bilowga
   • Waxay bannaysaa taako tallaabooyin waqti oo isku xigta ah
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. Halbeegkee ayay SpecAugment si gaar ah uga caawisay in la gaaro natiijooyin casri ah?
   • ImageNet
   • Hadal-qoraal
   • SQAD
   • Xabbad
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)