Kedis ku xidhan hagaha · Fudud Heerka

AI oo ku jira Qoraal-hoosaadka iyo Kediska Qoraal-qorista Xidhan

Dib u eegis ASR, waqti qoraal ah, khaladaadka hadalka, dib u eegis toos ah, tarjumaad, xawaaraha akhriska, iyo sababta saxnaanta qoraalka oo keliya aysan u hubin helitaanka.

Wadooyinka haga ee la xidhiidhaAI ee Qoraal-hoosaadka iyo Qoraal-bixinta xidhan
Su'aal 1 ee 8

Which information distinguishes accessibility captions from dialogue text alone?

Horudhac su'aal kasta8 su'aalo

Jawaabaha iyo sharraxaadaha waxay soo baxayaan markaad qaadanayso kediska.

  1. Which information distinguishes accessibility captions from dialogue text alone?
    • A requirement that every line use a yellow font
    • A requirement that captions never be selectable
    • Relevant non-speech sound cues and speaker identification when needed
    • The assumption that ASR already captures every visual detail
  2. Farsamogee ayaa marka hore maqalka ereyo u beddela?
    • Qoraal-ku-hadal
    • Kala soocidda sawirka
    • Aragtida mashiinka
    • Aqoonsiga hadalka tooska ah (ASR)
  3. Maxay tillaabada toosinta ku soo kordhinaysaa qoraalka?
    • Muusiga asalka ah
    • Astaamaha wakhtiga bilowga iyo dhamaadka saxda ah ee qoraal kasta
    • Turjumaadda Faransiiska
    • Ciwaanka muuqaalka
  4. Halbeegkee ayaa inta badan cabbira saxnaanta qoraalka?
    • Heerka Qaladka Erayga (WER)
    • Frames ilbiriqsikii
    • xallinta shaashadda
    • Cabbirka faylka
  5. Waa maxay sababta qoraalka tooska ah ay inta badan dib ugu eegto qoraalka ka dib marka ugu horraysa ee la muujiyo?
    • In lagu daro xayaysiisyada
    • Sababtoo ah waxay si dhakhso ah u soo saartaa natiijooyinka qayb ahaan, ka dibna waxay saxaysaa marka cod badan yimaado
    • Sababtoo ah daawadaha ayaa codsaday isbedel
    • Si loo turjumo luqado badan
  6. In a caption-localization pipeline, which stage converts the transcript into another language?
    • Timestamp alignment alone
    • Audio waveform resampling alone
    • Machine translation, followed by checking the translated text
    • Speaker clustering without text conversion
  7. Why should an AI captioning workflow adjust line breaks and reading speed after transcription?
    • Accurate words still need a readable on-screen presentation at the right time
    • Line breaks automatically fix every mistranscribed name
    • Reading speed determines the video's microphone sample rate
    • A correct transcript must be shown as one uninterrupted paragraph
  8. What remains to check when an automatic transcript has a low Word Error Rate?
    • Nothing, because WER certifies complete accessibility
    • Only the video's file extension
    • Whether every caption is exactly the same length
    • Caption synchronization, readability, speaker labels, and necessary non-speech cues