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Gradual acquisition (as per Connectionist model)
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| bet | 6/13 | | Sana | 01.05.2023 | | Hajmi | 62.11 Kb. | | #55474 |
Bog'liq Eldorni ishi namuna РАСУЛОВА М, Raxmatova Shaxsanam, Suyuqlikning muvozanatlik va harakat tenglamasi Reja, Iste\'molchilar yulduz va uchburchak shakllarda ulash, 39927, hyjhgj, F.Shubert ijodi, Mavzu O’zgarmas to’k dvigatellari va turlari ishlash prinsplari, Saparova Gulsanam , 4. Uglevodlar , Atsiklovir - Vikipediya, Kalendar reja, Zebo, Автокредит Полиси 149Gradual acquisition (as per Connectionist model)
Marcus et al. suggested that the first over-regularisation in each child’s corpus signals the moment of acquisition of the past tense rule, and state that this over-regularisation error is followed by “rapid increases in inflecting regulars to high levels shortly afterward. Adam’s first over-regularization occurred during a 3-month period in which regular marking increased from 0 to 100% Considering the data presented by Marcus et al. Hoeffner noted that one could just easily say that “Adam’s first over-regularization occurred during a six-month period in which the probability of using the regular … rose gradually from 24 to 44%”. Either statement seems fairly arbitrary; the data are noisy, and spikes occur when relatively few observations were available (Adam’s 100% marking at 37 months is based on 8 observations). Given the noise, the graphs from all three children suggest a process that proceeds from very little marking in obligatory contexts to fairly reliable marking over the course of about one year. A good fit to the data was achieved with a logistic regression in which the use of the regular past increases monotonically with age. Use of first over-regularization as a predictor did not reliably improve the account for regularization rates in any of the children. Moreover, the notion for past tense forms and grammar in general being “gradually acquired” rather than innate, finds support from Bayesian line of thought. “Gradually acquired” and “Probabilistic” can be related together since in Bayesian models, the beliefs are updated in light of new evidence which is a gradual process. Also, in ANN the networks are trained with the incoming data which is also a gradual process.
Domain specific (as per WR Model)
Certain cognitive functions are responsible for specific functions, related to modularity. Different types of information are learned differently [14, p. 139].
An intriguing aspect of inflection is that irregular forms can sometimes turn up in regular form. Some of these regularizations are unsystematic – For example, doublets such as dived/dove and dreamt/dreamed, in which the regular form is used sporadically because the irregular form is low in frequency and hence poorly remembered. But many are systematic: in particular contexts, the regular form is consistently used, such as ringed the city and low-lifes. The Words-and-Rules theory explains this phenomenon using an independently motivated theory of compositionality in word-formation [a,b] (see also Fig. 2 in main article).
Irregular-sounding words are regularized if they lack a root in the head position that can be marked for the inflectional feature (tense or number). The regular suffix applies as the default, as it does in other cases where memory access is disabled. This neatly explains a diverse set of systematic regularizations found in actual usages, laboratory experiments with adults and children, and many languages [15, p. 440].
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