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Salem, Alexandra C.; Gale, Robert; Casilio, Marianne; Fleegle, Mikala; Fergadiotis, Gerasimos; Bedrick, Steven – Journal of Speech, Language, and Hearing Research, 2023
Purpose: ParAlg (Paraphasia Algorithms) is a software that automatically categorizes a person with aphasia's naming error (paraphasia) in relation to its intended target on a picture-naming test. These classifications (based on lexicality as well as semantic, phonological, and morphological similarity to the target) are important for…
Descriptors: Semantics, Computer Software, Aphasia, Classification
Middleton, Erica L.; Chen, Qi; Verkuilen, Jay – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2015
The study of homophones--words with different meanings that sound the same--has great potential to inform models of language production. Of particular relevance is a phenomenon termed "frequency" inheritance, where a low-frequency word (e.g., "deer") is produced more fluently than would be expected based on its frequency…
Descriptors: Aphasia, Word Frequency, Phonology, Naming
Meffert, Elisabeth; Tillmanns, Eva; Heim, Stefan; Jung, Stefanie; Huber, Walter; Grande, Marion – Journal of Psycholinguistic Research, 2011
Two important research lines in neuro- and psycholinguistics are studying natural or experimentally induced slips of the tongue and investigating the symptom patterns of aphasic individuals. Only few studies have focused on explaining aphasic symptoms by provoking aphasic symptoms in healthy speakers. While all experimental techniques have so far…
Descriptors: Psycholinguistics, Models, Aphasia, Error Patterns
Duman, Tuba Yarbay; Bastiaanse, Roelien – Brain and Language, 2009
This study tested the production of tensed finite verbs and participles referring to the past and future in agrammatic speakers of Turkish. The agrammatic speakers did not make more time reference errors in tensed verbs than in participles. This is interesting because tense in general cannot therefore be the main problem, since time reference for…
Descriptors: Verbs, Turkish, Neurolinguistics, Aphasia
Bormann, Tobias; Kulke, Florian; Wallesch, Claus-W.; Blanken, Gerhard – Brain and Language, 2008
Within a discrete two-stage model of lexicalization, semantic errors and errors of omission are assumed to be independent events. In contrast, cascading and interactive models allow for an influence of word form on lexical selection and thus for an inherent relationship in accounting for both error types. A group of 17 aphasic patients was…
Descriptors: Semantics, Aphasia, Patients, Semiotics
Jokel, Regina; Rochon, Elizabeth; Leonard, Carol – Brain and Cognition, 2004
This paper presents preliminary results of pre- and post-treatment error analysis from an aphasic patient with anomia. The Interactive Activation (IA) model of word production (Dell, Schwartz, Martin, Saffran, & Gagnon, 1997) is utilized to make predictions about the anticipated changes on a picture naming task and to explain emerging patterns.…
Descriptors: Prediction, Error Patterns, Error Analysis (Language), Aphasia

Harley, Trevor A.; And Others – Language and Cognitive Processes, 1995
This article explores a model of lexicalisation based upon the constraints that lexicalisation is an interactive process and that it takes place in two stages. The article examines in depth the time-course of normal lexicalisation, speech error data, and the cognitive neuropsychology of speech production. (16 references) (CK)
Descriptors: Aphasia, Cognitive Structures, Error Patterns, Generative Phonology