Maswali yanayounganishwa na mwongozo · Kati Kiwango

Maswali ya Maneno ya Kuchunguza na Kuamsha Maneno

Kagua utambuaji wa maneno muhimu, ugunduzi wa ghafla, kukubalika kwa uwongo, vipengele vya sauti, uaminifu wa muda na vikwazo vya kifaa.

Njia za mwongozo zinazohusianaKeyword Spotting Na Wake Maneno
Swali 1 ya 8

Je, kazi ya msingi ya kigunduzi cha maneno ya kuamsha ni nini?

Hakiki kila swali8 maswali

Majibu na maelezo huonekana unapojibu maswali.

  1. Je, kazi ya msingi ya kigunduzi cha maneno ya kuamsha ni nini?
    • Ili kugundua wakati kishazi mahususi cha kianzishi kimezungumzwa
    • Ili kunakili kila neno ambalo mtumiaji anasema kwa maandishi
    • Ili kutafsiri hotuba katika lugha nyingine
    • Ili kubana sauti kwa hifadhi ya wingu
  2. Kwa nini wazungumzaji wengi mahiri hutumia muundo wa ugunduzi wa hatua mbili?
    • Ili kusaidia lugha mbili tofauti mara moja
    • Kuruhusu chipu ya nishati ya chini ichunguze kabla ya muundo mkubwa kuthibitisha, kuokoa betri
    • Ili kurekodi nakala mbili za sauti kwa nakala rudufu
    • Kuendesha visaidizi viwili tofauti vya sauti kwa wakati mmoja
  3. 'Kukubali kwa uwongo' kunamaanisha nini katika ugunduzi wa maneno-wake?
    • Kifaa hupuuza kifungu cha vichochezi kinachotamkwa kwa usahihi
    • Kifaa hukosea neno moja kama lingine katika sentensi
    • Kifaa huamka ingawa hakuna mtu aliyesema maneno ya kuchochea
    • Kifaa kinashindwa kuunganishwa kwenye mtandao
  4. Takriban ni jinsi gani sauti inayoingia inatayarishwa kabla ya mtandao wa neva kuiona?
    • Inahifadhiwa kama faili ya MP3 ya urefu kamili kwanza
    • Inabadilishwa moja kwa moja kuwa sentensi zilizoandikwa
    • Inatumwa bila kubadilishwa kwa seva ya mbali kwa uchambuzi
    • Imekatwa katika fremu fupi zinazopishana na kugeuzwa kuwa vipengele vya akustisk kama vile MFCCs au mel energy.
  5. What trade-off can raising a wake-word detector’s activation threshold create?
    • Fewer false accepts but potentially more false rejects or delayed detections
    • More false accepts and guaranteed zero false rejects
    • No change in either error rate under any audio condition
    • A guarantee that every user’s phrase is recognized
  6. What result did Hello Edge report for its depthwise separable CNN on the Google Speech Commands evaluation?
    • 100% accuracy on all languages and devices
    • 95.4% accuracy, about 10% higher than a DNN with a similar parameter count
    • 95.4% lower memory use than every competing model
    • A 10% guaranteed battery-life increase for every microcontroller
  7. What does a false reject mean in wake-word detection?
    • The detector activates without the wake word
    • The microphone records silence correctly
    • The user says the wake word but the detector does not activate
    • A speaker is assigned the wrong identity
  8. Why may a wake-word system use a compact model on-device?
    • It guarantees zero false accepts
    • It replaces all speech recognition
    • It makes the wake phrase unnecessary
    • It can reduce dependence on network access and support low-power always-on detection