ASL fingerspelling translator

This ASL fingerspelling translator encodes plain text into stable snake_case handshape tokens, decodes those tokens back into letters and digits, and reports every character that has no standard fingerspelling handshape instead of failing the whole request.

Encode text into ASL fingerspelling handshape names

Identical inputs always produce identical outputs because the path is pure table lookup with no network, no random salt, and no wall clock. Use encode whenever you need a paste-ready study sheet, flash-card back, or UI caption that names each handshape without embedding video. Send a JSON body with the required string field text set to the letters and digits you want to fingerspell, and leave mode at its default encode or set mode to encode explicitly. Each Latin letter A through Z maps to a canonical handshape token such as fist_a for A, flat_b for B, curved_c for C, pinky_i for I, cross_r for R, and y_shape for Y, following common ASL teaching charts for the static one-handed alphabet. Digits zero through nine map to distinct numeral tokens such as zero_o, one_index, two_v, three_thumb, four_fingers, five_open, six_pinky, seven_ring, eight_middle, and nine_ok so a mixed serial like AB12 does not collide with letter forms on round-trip. Whitespace in the input separates word groups: handshapes inside a group are joined with single spaces, and groups are joined with a slash surrounded by spaces so Hi there becomes horizontal_h pinky_i slash fist_t horizontal_h claw_e cross_r claw_e. Characters outside letters and digits—punctuation, currency symbols, emoji, and non-Latin scripts—do not abort the request; they appear in the no_handshape array with the original character and its zero-based index, and no_handshape_count reports how many were skipped. Aliases input, value, and s are accepted for the text field; direction, op, and action may stand in for mode. The response includes result as the handshape phrase, tokens as an array of char and handshape pairs for every mapped character, count as the number of mapped characters, mode equal to encode, and alphabet equal to asl_fingerspell.

Decode handshape tokens and handle unknown labels

Set mode to decode and put a sequence of ASL fingerspelling handshape tokens in text, separated by spaces. Optional slash markers between word groups are ignored so you can round-trip the encode output without stripping separators by hand. Empty decode input fails the same way. Prefer this capability when search intent is ASL fingerspelling, American Sign Language alphabet handshapes, fingerspell translator, or letter-to-handshape converter; full ASL sentence translation, mouthing, and non-manual markers belong to language-learning tools, not this table. Matching is case-insensitive and treats hyphens, underscores, and internal spaces as equivalent, so fist_a, Fist-A, and fist a all decode to A. Canonical tokens resolve to uppercase letters and digit characters; friendly aliases such as flat_hand for B, ok_sign for F, peace for V, letter-only shortcuts a through z, and digit_0 through digit_9 are accepted so real-world pastes from notes still work. Any token that is not a known handshape name raises invalid_input with an explicit unknown handshape message naming the bad token—exactly the contract quiz graders and flash-card importers need when a typo would otherwise invent a wrong letter. On success the response returns result as the recovered string, tokens pairing each resolved character with its canonical handshape label, count, mode decode, and alphabet asl_fingerspell. Validation failures are not charged on the prepaid API, so operators can probe bad pastes safely.

API usage, pricing, workflows, and practical limits

Call the free in-browser ASL fingerspelling translator for classroom drills, interpreter practice sheets, name badges that list handshapes beside Latin letters, and one-off checks of a product code without installing a spreadsheet of shapes. Another workflow decodes quiz answers and fails loud on unknown handshape tokens so instructors see the exact typo. Authors shipping SDKs can map the tokens array into a table of character and handshape columns for UI copy buttons, while mode and alphabet labels make OpenAPI examples self-explanatory for readers comparing fingerspelling systems across signed languages. Use the prepaid KIT API when a learning management system, accessibility glossary builder, mobile study app, or SDK needs the same encode or decode step under balance at $0.002 per successful item; failed validation never consumes balance after the engine rejects the request. A typical workflow encodes a learner’s name for a printable study card, shows no_handshape entries when the paste included a hyphen or apostrophe, then decodes the student-typed token list and asserts that result matches the original letters. Pair this endpoint with uppercase or transliteration tools when identifiers arrive in mixed scripts, but keep the steps separate so each landing page matches a single search intent.