wordsignfactor

Wordsignfactor is a coined metric in linguistics and sign language studies that denotes a numerical value expressing the strength of association between a spoken or written word and its sign-language counterpart within a corpus, lexicon, or experimental dataset. The concept aims to quantify how consistently a particular sign maps to a given word or how strongly a word evokes a specific sign across signers. In operational terms, the score can be derived from measures such as normalized mutual information, translation alignment probability, or perceptual ratings of sign-lexicality, and is often normalized on a standard scale (for example 0 to 1).

Applications include constructing sign language dictionaries, training automated sign language translation systems, and conducting psycholinguistic experiments on sign iconicity and lexical access.

Calculation and variability: word-sign factor can be computed from sign-language corpora, aligned sign-and-word datasets, or elicitation studies. It can vary by signer, dialect, and modality (single-sign vs. compound signs; fingerspelling).

Limitations: the term is not standardized; depends on dataset and methodology; sign languages differ widely; not all words have a single canonical sign.

Example: In ASL, common content words such as "mother" or "water" may show high wordsignfactors, while abstract terms may have lower due to polysemy or multiple signs.

See also: sign language linguistics; lexicon; iconicity; machine translation; alignment modeling.