Guide-linked quiz · Medium Level

AI in Sign Language Translation Quiz

Review signed-language grammar, non-manual markers, pose features, continuous alignment, gloss notation, and the scope of a translation benchmark.

Question 1 of 8

Why does translating a signed language require more than a gesture-to-English-word lookup?

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Answers and explanations appear as you take the quiz.

  1. Why does translating a signed language require more than a gesture-to-English-word lookup?
    • Every sign follows the same word order as spoken English
    • Signed languages have their own grammatical and spatial structures
    • Handshape recognition alone captures every linguistic feature
    • Each sign always corresponds to exactly one English word
  2. What are 'non-manual markers' in sign languages?
    • Special gloves worn by signers
    • Written subtitles added to videos
    • Hand sanitizer used before signing
    • Facial expressions and body movements that carry grammatical meaning
  3. In a pose-based sign-language pipeline, what does keypoint extraction produce from video frames?
    • Coordinates describing selected hand, face, and body landmarks
    • A guaranteed complete translation with no sequence model
    • A rule that the original video has already been deleted
    • Only the recording's file size and filename
  4. Why does continuous sign-language recognition need to address temporal alignment?
    • Every sign is a static image with no temporal information
    • Signed languages contain no grammatical structure
    • Signs and transitions can coarticulate without an obvious pause at every boundary
    • A video's frame rate reveals the target sentence without interpretation
  5. A major bottleneck for training these systems is:
    • Too many high-quality labeled datasets
    • Cameras being illegal
    • Sign languages having no grammar
    • A shortage of large, annotated sign language datasets
  6. What does involving Deaf communities and language experts add when designing sign-language AI tools?
    • A guarantee that all signed languages share the same grammar
    • Knowledge of real needs and linguistic and cultural context for design and evaluation
    • Elimination of the need to evaluate translations
    • A reason to assume one laboratory benchmark covers every signer
  7. What does a gloss annotation represent in the sign-language research pipeline described here?
    • A universal spoken-language sentence that every signed language uses
    • Only a camera's color profile
    • A textual label for a sign, rather than a complete grammatical spoken-language translation
    • A guarantee that all facial grammar has been fully preserved
  8. Which language and domain characterize the PHOENIX-2014T benchmark introduced in the cited 2018 work?
    • German Sign Language weather broadcasts paired with German text
    • Every signed language recorded in all clinical settings
    • Only English speech recordings with no signing video
    • Only static photographs of handwritten alphabets

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