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.
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.
Speech recognitionSpeech recognition is an interdisciplinary subfield of computer science and computational linguistics that develops methodologies and technologies that enable the recognition and translation of spoken language into text by computers. It is also known as automatic speech recognition (ASR), computer speech recognition or speech to text (STT). It incorporates knowledge and research in the computer science, linguistics and computer engineering fields. The reverse process is speech synthesis.
Writing systemA writing system is a method of visually representing verbal communication, based on a script and a set of rules regulating its use. While both writing and speech are useful in conveying messages, writing differs in also being a reliable form of information storage and transfer. Writing systems require shared understanding between writers and readers of the meaning behind the sets of characters that make up a script.
Dual-route hypothesis to reading aloudThe dual-route theory of reading aloud was first described in the early 1970s. This theory suggests that two separate mental mechanisms, or cognitive routes, are involved in reading aloud, with output of both mechanisms contributing to the pronunciation of a written stimulus. The lexical route is the process whereby skilled readers can recognize known words by sight alone, through a "dictionary" lookup procedure. According to this model, every word a reader has learned is represented in a mental database of words and their pronunciations that resembles a dictionary, or internal lexicon.
ASCIIASCII (ˈæskiː ), abbreviated from American Standard Code for Information Interchange, is a character encoding standard for electronic communication. ASCII codes represent text in computers, telecommunications equipment, and other devices. Because of technical limitations of computer systems at the time it was invented, ASCII has just 128 code points, of which only 95 are , which severely limited its scope. Many computer systems instead use Unicode, which has millions of code points, but the first 128 of these are the same as the ASCII set.
Czech orthographyCzech orthography is a system of rules for proper formal writing (orthography) in Czech. The earliest form of separate Latin script specifically designed to suit Czech was devised by Czech theologian and church reformist Jan Hus, the namesake of the Hussite movement, in one of his seminal works, De orthographia bohemica (On Bohemian orthography). The modern Czech orthographic system is diacritic, having evolved from an earlier system which used many digraphs (although one digraph has been kept - ch).
Deep learningDeep learning is part of a broader family of machine learning methods, which is based on artificial neural networks with representation learning. The adjective "deep" in deep learning refers to the use of multiple layers in the network. Methods used can be either supervised, semi-supervised or unsupervised.
Bengali languageBengali (bɛnˈɡɔːli ), generally known by its endonym Bangla (বাংলা, ˈbaŋla), is an Indo-Aryan language native to the Bengal region of South Asia. With approximately 300 million native speakers and another 50 million as second language speakers, Bengali is the sixth most spoken native language and the seventh most spoken language by the total number of speakers in the world. Bengali is the fifth most spoken Indo-European language. Bengali is the official, national, and most widely spoken language of Bangladesh, with 98% of Bangladeshis using Bengali as their first language.
Acoustic modelAn acoustic model is used in automatic speech recognition to represent the relationship between an audio signal and the phonemes or other linguistic units that make up speech. The model is learned from a set of audio recordings and their corresponding transcripts. It is created by taking audio recordings of speech, and their text transcriptions, and using software to create statistical representations of the sounds that make up each word. Modern speech recognition systems use both an acoustic model and a language model to represent the statistical properties of speech.
Hidden Markov modelA hidden Markov model (HMM) is a statistical Markov model in which the system being modeled is assumed to be a Markov process — call it — with unobservable ("hidden") states. As part of the definition, HMM requires that there be an observable process whose outcomes are "influenced" by the outcomes of in a known way.
Varieties of ArabicThe varieties (or dialects or vernacular languages) of Arabic, a Semitic language within the Afroasiatic family originating in the Arabian Peninsula, are the linguistic systems that Arabic speakers speak natively. There are considerable variations from region to region, with degrees of mutual intelligibility that are often related to geographical distance and some that are mutually unintelligible. Many aspects of the variability attested to in these modern variants can be found in the ancient Arabic dialects in the peninsula.
Markov modelIn probability theory, a Markov model is a stochastic model used to model pseudo-randomly changing systems. It is assumed that future states depend only on the current state, not on the events that occurred before it (that is, it assumes the Markov property). Generally, this assumption enables reasoning and computation with the model that would otherwise be intractable. For this reason, in the fields of predictive modelling and probabilistic forecasting, it is desirable for a given model to exhibit the Markov property.
ReadingReading is the process of taking in the sense or meaning of letters, symbols, etc., especially by sight or touch. For educators and researchers, reading is a multifaceted process involving such areas as word recognition, orthography (spelling), alphabetics, phonics, phonemic awareness, vocabulary, comprehension, fluency, and motivation. Other types of reading and writing, such as pictograms (e.g., a hazard symbol and an emoji), are not based on speech-based writing systems.
Synthetic phonicsSynthetic phonics, also known as blended phonics or inductive phonics, is a method of teaching English reading which first teaches the letter sounds and then builds up to blending these sounds together to achieve full pronunciation of whole words. Synthetic phonics refers to a family of programmes which aim to teach reading and writing through the following methods: Teaching students the correspondence between written letters (graphemes) and speech sounds (phonemes).
Analytic phonicsAnalytic phonics (sometimes referred to as analytical phonics or implicit phonics) refers to a very common approach to the teaching of reading that starts at the word level, not at the sound (phoneme) level. It does not teach the blending of sounds together as is done in synthetic phonics. One method is to have students identify a common sound in a set of words that each contain that same sound. For example, the teacher and student discuss how the following words are alike: pat, park, push and pen.
Context-free languageIn formal language theory, a context-free language (CFL) is a language generated by a context-free grammar (CFG). Context-free languages have many applications in programming languages, in particular, most arithmetic expressions are generated by context-free grammars. Different context-free grammars can generate the same context-free language. Intrinsic properties of the language can be distinguished from extrinsic properties of a particular grammar by comparing multiple grammars that describe the language.
Context-free grammarIn formal language theory, a context-free grammar (CFG) is a formal grammar whose production rules can be applied to a nonterminal symbol regardless of its context. In particular, in a context-free grammar, each production rule is of the form with a single nonterminal symbol, and a string of terminals and/or nonterminals ( can be empty). Regardless of which symbols surround it, the single nonterminal on the left hand side can always be replaced by on the right hand side.
IdeasthesiaIdeasthesia (alternative spelling ideaesthesia) is a neuropsychological phenomenon in which activations of concepts (inducers) evoke perception-like sensory experiences (concurrents). The name comes from the Ancient Greek ἰδέα (idéa) and αἴσθησις (aísthēsis), meaning 'sensing concepts' or 'sensing ideas'. The notion was introduced by neuroscientist Danko Nikolić as an alternative explanation for a set of phenomena traditionally covered by synesthesia.
