quiz bu lëkkale ak tegtal · Diggante Niveau

IA ci Sistemu Recommandation Quiz

Natt jëfandikoo siñaal lëkkaloo yi, man-mani audio yi, limu playlist yi, barabi samp yi ak mébetu gis-gis yi.

Yooni njiit yu jëm ciIA ci sistem yiy xelal music
Laaj 1 de 8

Lan mooy jafe-jafe 'tàmbali bu sedd' ci digle music?

Xoolaatal laaj bu nekk8 laaj

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

  1. Lan mooy jafe-jafe 'tàmbali bu sedd' ci digle music?
    • Jafe-jafe bi mooy xelal way yu bees wala jëfandikukat yu amul jaar-jaar déglu
    • Way yu ñuy jouer ndànk lool
    • Serveur yi dañuy daanu ci hiver bi
    • Limu playlist yu gudd lool
  2. How can content-based audio analysis help recommend a new or little-heard song?
    • By relying only on the new track’s total number of past plays
    • By comparing audio-derived representations with tracks that match a listener’s musical preferences
    • By matching its file size to songs in the same playlist
    • By using the song’s upload date as its only similarity signal
  3. Seggal lëkkaloo dafay njëkka dox ci gis lan?
    • Way yu tolloo guddaay
    • Piste yi gëna yomb
    • Déglukat yu am jikko yu noonu mel, di wax li ñu bëgg
    • Way yi ci rang alfabet
  4. Ci sistem yu lalu ci embedding, ñaari way dañuy nuru sudee seeni vecteur ñooy lan?
    • Guddaay bu benn buum
    • Kulòor yu wuute
    • Ñu ngi ko denc ci benn serwër bi
    • Jegewaale ci barab bi ñu bokk
  5. Lan la projet génome musical bu Pandora gëm bu baax?
    • Etiketu màndarga musical bu leer ci way yi
    • mélangage aléatoire
    • Siiwal artist bi kese
    • Adres email jëfandikukat bi
  6. Lan moo waral platform yi di gëna bàyyi xel ci yoon ci seeni xalaat?
    • Ngir gëna gàtt limu playlist yi
    • Ngir moytu gëna dooleel ay mega-hit yu néew, jàppale artist yu ndaw yi ñu gis leen
    • Ngir wàññi dayo fichier yi
    • Ngir yeexal lees
  7. What does playlist co-occurrence contribute to a music recommender?
    • A measurement of the track’s audio sample rate
    • A prediction of how much storage a song requires
    • Context about which tracks listeners place together in playlists
    • A replacement for listening-history data
  8. Why is nearest-neighbor search useful after music tracks are mapped into an embedding space?
    • It transcribes every track’s lyrics first
    • It changes the recording’s sample rate
    • It selects songs by file name only
    • It can quickly retrieve tracks whose vectors are close to a user’s vector