Letter (alphabet)A letter is a segmental symbol of a phonemic writing system. The inventory of all letters forms an alphabet. Letters broadly correspond to phonemes in the spoken form of the language, although there is rarely a consistent and exact correspondence between letters and phonemes. The word letter, borrowed from Old French letre, entered Middle English around 1200 AD, eventually displacing the Old English term bōcstæf (bookstaff). Letter is descended from the Latin littera, which may have descended from the Greek "διφθέρα" (, writing tablet), via Etruscan.
Speaker recognitionSpeaker recognition is the identification of a person from characteristics of voices. It is used to answer the question "Who is speaking?" The term voice recognition can refer to speaker recognition or speech recognition. Speaker verification (also called speaker authentication) contrasts with identification, and speaker recognition differs from speaker diarisation (recognizing when the same speaker is speaking).
Markov propertyIn probability theory and statistics, the term Markov property refers to the memoryless property of a stochastic process, which means that its future evolution is independent of its history. It is named after the Russian mathematician Andrey Markov. The term strong Markov property is similar to the Markov property, except that the meaning of "present" is defined in terms of a random variable known as a stopping time. The term Markov assumption is used to describe a model where the Markov property is assumed to hold, such as a hidden Markov model.
PhonotacticsPhonotactics (from Ancient Greek phōnḗ "voice, sound" and taktikós "having to do with arranging") is a branch of phonology that deals with restrictions in a language on the permissible combinations of phonemes. Phonotactics defines permissible syllable structure, consonant clusters and vowel sequences by means of phonotactic constraints. Phonotactic constraints are highly language-specific. For example, in Japanese, consonant clusters like /st/ do not occur.
Markov chainA Markov chain or Markov process is a stochastic model describing a sequence of possible events in which the probability of each event depends only on the state attained in the previous event. Informally, this may be thought of as, "What happens next depends only on the state of affairs now." A countably infinite sequence, in which the chain moves state at discrete time steps, gives a discrete-time Markov chain (DTMC). A continuous-time process is called a continuous-time Markov chain (CTMC).
English phonologyEnglish phonology is the system of speech sounds used in spoken English. Like many other languages, English has wide variation in pronunciation, both historically and from dialect to dialect. In general, however, the regional dialects of English share a largely similar (but not identical) phonological system. Among other things, most dialects have vowel reduction in unstressed syllables and a complex set of phonological features that distinguish fortis and lenis consonants (stops, affricates, and fricatives).
Latin scriptThe Latin script, also known as the Roman script, is an alphabetic writing system based on the letters of the classical Latin alphabet, derived from a form of the Greek alphabet which was in use in the ancient Greek city of Cumae, in southern Italy (Magna Graecia). The Greek alphabet was adopted by the Etruscans, and subsequently their alphabet was adopted by the Romans. Several Latin-script alphabets exist, which differ in graphemes, collation and phonetic values from the classical Latin alphabet.
Probabilistic context-free grammarGrammar theory to model symbol strings originated from work in computational linguistics aiming to understand the structure of natural languages. Probabilistic context free grammars (PCFGs) have been applied in probabilistic modeling of RNA structures almost 40 years after they were introduced in computational linguistics. PCFGs extend context-free grammars similar to how hidden Markov models extend regular grammars. Each production is assigned a probability.
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.
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.
Sentence processingSentence processing takes place whenever a reader or listener processes a language utterance, either in isolation or in the context of a conversation or a text. Many studies of the human language comprehension process have focused on reading of single utterances (sentences) without context. Extensive research has shown that language comprehension is affected by context preceding a given utterance as well as many other factors. Sentence comprehension has to deal with ambiguity in spoken and written utterances, for example lexical, structural, and semantic ambiguities.
PsycholinguisticsPsycholinguistics or psychology of language is the study of the interrelation between linguistic factors and psychological aspects. The discipline is mainly concerned with the mechanisms by which language is processed and represented in the mind and brain; that is, the psychological and neurobiological factors that enable humans to acquire, use, comprehend, and produce language. Psycholinguistics is concerned with the cognitive faculties and processes that are necessary to produce the grammatical constructions of language.
