Phonemic orthographyA phonemic orthography is an orthography (system for writing a language) in which the graphemes (written symbols) correspond to the phonemes (significant spoken sounds) of the language. Natural languages rarely have perfectly phonemic orthographies; a high degree of grapheme–phoneme correspondence can be expected in orthographies based on alphabetic writing systems, but they differ in how complete this correspondence is.
Multilayer perceptronA multilayer perceptron (MLP) is a misnomer for a modern feedforward artificial neural network, consisting of fully connected neurons with a nonlinear kind of activation function, organized in at least three layers, notable for being able to distinguish data that is not linearly separable. It is a misnomer because the original perceptron used a Heaviside step function, instead of a nonlinear kind of activation function (used by modern networks).
GraphemeIn linguistics, a grapheme is the smallest functional unit of a writing system. The word grapheme is derived and the suffix -eme by analogy with phoneme and other names of emic units. The study of graphemes is called graphemics. The concept of graphemes is abstract and similar to the notion in computing of a character. By comparison, a specific shape that represents any particular grapheme in a given typeface is called a glyph. There are two main opposing grapheme concepts.
PhonemeIn phonology and linguistics, a phoneme (ˈfoʊniːm) is a unit of phone that can distinguish one word from another in a particular language. For example, in most dialects of English, with the notable exception of the West Midlands and the north-west of England, the sound patterns sɪn (sin) and sɪŋ (sing) are two separate words that are distinguished by the substitution of one phoneme, /n/, for another phoneme, /ŋ/. Two words like this that differ in meaning through the contrast of a single phoneme form a minimal pair.
GlyphA glyph (ɡlɪf) is any kind of purposeful mark. In typography, a glyph is "the specific shape, design, or representation of a character". It is a particular graphical representation, in a particular typeface, of an element of written language. A grapheme, or part of a grapheme (such as a diacritic), or sometimes several graphemes in combination (a composed glyph) can be represented by a glyph. In most languages written in any variety of the Latin alphabet except English, the use of diacritics to signify a sound mutation is common.
OrthographyAn orthography is a set of conventions for writing a language, including norms of spelling, hyphenation, capitalization, word boundaries, emphasis, and punctuation. Most transnational languages in the modern period have a writing system, and most of these systems have undergone substantial standardization, thus exhibiting less dialect variation than the spoken language. These processes can fossilize pronunciation patterns that are no longer routinely observed in speech (e.g.
PerceptronIn machine learning, the perceptron (or McCulloch-Pitts neuron) is an algorithm for supervised learning of binary classifiers. A binary classifier is a function which can decide whether or not an input, represented by a vector of numbers, belongs to some specific class. It is a type of linear classifier, i.e. a classification algorithm that makes its predictions based on a linear predictor function combining a set of weights with the feature vector.
Perceptrons (book)Perceptrons: an introduction to computational geometry is a book written by Marvin Minsky and Seymour Papert and published in 1969. An edition with handwritten corrections and additions was released in the early 1970s. An expanded edition was further published in 1987, containing a chapter dedicated to counter the criticisms made of it in the 1980s. The main subject of the book is the perceptron, a type of artificial neural network developed in the late 1950s and early 1960s.
Feedforward neural networkA feedforward neural network (FNN) is one of the two broad types of artificial neural network, characterized by direction of the flow of information between its layers. Its flow is uni-directional, meaning that the information in the model flows in only one direction—forward—from the input nodes, through the hidden nodes (if any) and to the output nodes, without any cycles or loops, in contrast to recurrent neural networks, which have a bi-directional flow.
Orthographic depthThe orthographic depth of an alphabetic orthography indicates the degree to which a written language deviates from simple one-to-one letter–phoneme correspondence. It depends on how easy it is to predict the pronunciation of a word based on its spelling: shallow orthographies are easy to pronounce based on the written word, and deep orthographies are difficult to pronounce based on how they are written. In shallow orthographies, the spelling-sound correspondence is direct: from the rules of pronunciation, one is able to pronounce the word correctly.
