In European folklore and folk-belief of the Medieval and Early Modern periods, familiar spirits (sometimes referred to simply as "familiars" or "animal guides") were believed to be supernatural entities that would assist witches and cunning folk in their practice of magic. According to the records of the time, they would appear in numerous guises, often as an animal, but also at times as a human or humanoid figure, and were described as "clearly defined, three-dimensional… forms, vivid with colour and animated with movement and sound" by those alleging to have come into contact with them, unlike later descriptions of ghosts with their "smoky, undefined form[s]".
The library basically replicates what the application itself does when you create flashcards via the gui, except uses ruby’s sqlite package to create flashcards and bundle media files together.
With a combination of this and some jQuery, its pretty easy to grab all the phrases + sound files for a language and create flashcards for them.
Our ability to remember a piece of information depends critically on the number of times we have reviewed it, the temporal distribution of the reviews, and the time elapsed since the last review, as first shown by a seminal study by Ebbinghaus (1). The effect of these two factors has been extensively investigated in the experimental psychology literature (2, 3), particularly in second language acquisition research (4⇓⇓–7). Moreover, these empirical studies have motivated the use of flashcards, small pieces of information a learner repeatedly reviews following a schedule determined by a spaced repetition algorithm (8), whose goal is to ensure that learners spend more (less) time working on forgotten (recalled) information.
However, current spaced repetition algorithms are simple rule-based heuristics with a few hard-coded parameters. Here, we introduce a flexible representation of spaced repetition using the framework of marked temporal point processes and then address the design of spaced repetition algorithms with provable guarantees as an optimal control problem for stochastic differential equations with jumps.