The model learns the two tasks simultaneously and handles un- known words via embeddings. It casts a word or a definition to the same representation space.

May 9, 2022 · It casts a word or a definition to the same representation space through a shared layer, then generates the other form in a multi-task fashion.

The model learns to encode definitions and words using a shared layer, and then generates both forms via multi-tasking to accomplish reverse dictionary.

We build a dual-way neural dictionary to retrieve words given definitions, and produce definitions for queried words. The model learns the two tasks ...

This paper showcases the work that aims at building a user-friendly mobile application of a reverse dictionary to translate sign languages to spoken languages.

Oct 11, 2022 · We build a multi-task model for reverse dictionary and definition modelling. The approach records strong numbers on public datasets. Our method.

A Unified Model for Reverse Dictionary and Definition Modelling ... We build a dual-way neural dictionary to retrieve words given definitions, and produce ...

Abstract. We train a dual-way neural dictionary to guess words from definitions (reverse dictionary), and produce definitions given words (defini-.

A reverse dictionary takes the description of a target word as input and outputs the target word together with other words that match the description.

It starts with a given root word that the player must define. The player must recursively define all new words in the definitions, until all words are defined. ...