SpecAugment kwa Maswali ya Utambuzi wa Usemi

Majibu na maelezo huonekana unapojibu maswali.

1. Je, SpecAugment inafanya kazi gani?
   • Mtazamo wa log-mel
   • Mtindo mbichi wa wimbi la sauti
   • Nakala ya maandishi
   • Uzito wa mfano
2. Ni ipi kati ya hizi ni moja ya shughuli tatu za SpecAugment?
   • Ugeuzaji wa lami
   • Masking ya mara kwa mara
   • Ubadilishaji wa maneno
   • Sindano ya 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. Je! 'Masking ya wakati' hufanya nini?
   • Hufuta alama za nyakati za manukuu
   • Huongeza kasi ya uchezaji wa sauti
   • Huondoa ukimya mwanzoni
   • Inafuta muda wa hatua za wakati mfululizo
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. Je, SpecAugment ilisaidia kwa kiwango gani kufikia matokeo ya hali ya juu?
   • Picha ya Picha
   • LibriSpeech
   • KIKOSI
   • GUNDI
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)