quiz bu lëkkale ak tegtal · Diggante Niveau

Audio ak Representation buy Jàngale Quiz

Xoolaat ni embeddings audio yi di kodee son, ni tàggat yaram bu wuute di lëkkale audio ak mbind, ak ni vecteur yiñ jàng di toxalee ci liggéey yi.

Laaj 1 de 8

Luy dugal audio?

Xoolaatal laaj bu nekk8 laaj

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

  1. Luy dugal audio?
    • Vecteur bu am guddaay bu takku buy màndargaal màndarga yu am solo yi ci benn son
    • Benn xeetu MP3 buñ komprime ci fichier audio bi
    • Transkripsioŋ buñ bind ci kàddu yiñ wax
    • Niveau volume buñuy natt ci desibel
  2. Lan moo tax jàng bi ñuy saytu sa bopp am solo lool ci embedding audio yi?
    • Dafay laaj ñu enregistre audio ci studio
    • Dafay jàng misaal yu am njariñ ci audio buñu etiketuwul, wàññi soxla etiketu nit
    • Music rek lay dox, du wax
    • Dafay garanti transkripsioŋ bu jaar yoon
  3. naka la Wav2Vec 2.0 di jàngee ci diiru tàggat yaram?
    • Tekki audio ci français
    • Ni ngay jottali bépp fichier de formation ci sa bopp
    • Ni ñuy maskeer span audio yi ak di wax luy waaja am ci distracteur yi
    • Ni ñuy nattee dayo fichier bu clip bu nekk
  4. Lan mooy model bu melni CLAP ci barab buñ bokk?
    • Ñaari kadre wideo yu wuute
    • Pixel yi ak histogram melo yi
    • Niveau batëri ak jëfandikoo CPU
    • Audio ak bind yu méngoo
  5. Laata ñuy dugal audio ci reso neuronal, ban coppite lañuy faral di jëfandikoo?
    • Soppi ko ci spectrogram wala filtre buñ jàng
    • Imprime ko ni partition
    • efaase bépp fréquence bu ëpp déglu nit
    • Soppi ko ci nataalu JPEG bu muur albom bi
  6. Ban liggéey ci àdduna bi mooy gëna aju ci méngale embeddings audio yi?
    • Xayma njëgu jënd benn way
    • Waxkat bi diarization, xam kan moo wax kañ
    • Tann art bu albom bi
    • Regler leeralu ekraŋ bi
  7. During contrastive audio-text training, what happens to a matching audio clip and its text description?
    • They are converted into the same raw waveform
    • The text embedding is discarded
    • Their embeddings are pulled closer while mismatched pairs are pushed apart
    • The audio is assigned a speaker name as a class label
  8. Why can one self-supervised audio embedding be reused across several downstream tasks?
    • It stores the original waveform without compression
    • It contains a manually written label for every possible sound
    • It works only for one speaker and one recording
    • It captures general acoustic structure that can support tasks with little extra labeled data