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Models of language processing can be used to conceptualize the nature of impairment in persons with speech and language disorder. For example, it has been suggested that language deficits in expressive aphasia may be caused by excessive competition between lexical units, thus preventing any word from becoming sufficiently activated. [9 ...
The lexical route is the process whereby skilled readers can recognize known words by sight alone, through a "dictionary" lookup procedure. [1] [4] 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.
The cohort model is based on the concept that auditory or visual input to the brain stimulates neurons as it enters the brain, rather than at the end of a word. [5] This fact was demonstrated in the 1980s through experiments with speech shadowing, in which subjects listened to recordings and were instructed to repeat aloud exactly what they heard, as quickly as possible; Marslen-Wilson found ...
Speech perception research has applications in building computer systems that can recognize speech, in improving speech recognition for hearing- and language-impaired listeners, and in foreign-language teaching. The process of perceiving speech begins at the level of the sound signal and the process of audition.
The methods of neuro-linguistic programming are the specific techniques used to perform and teach neuro-linguistic programming, [1] [2] which teaches that people are only able to directly perceive a small part of the world using their conscious awareness, and that this view of the world is filtered by experience, beliefs, values, assumptions, and biological sensory systems.
A classic example of computational modeling in language research is McClelland and Elman's TRACE model of speech perception. [13] A model of sentence processing can be found in Hale (2011)'s 'rational' Generalized Left Corner parser. [14] This model derives garden path effects as well as local coherence phenomena.
A language model is a probabilistic model of a natural language. [1] In 1980, the first significant statistical language model was proposed, and during the decade IBM performed ‘Shannon-style’ experiments, in which potential sources for language modeling improvement were identified by observing and analyzing the performance of human subjects in predicting or correcting text.
Speech 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).