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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- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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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