The Patterns Of Language

The human brain is capable of perceiving and interpreting information or stimuli received through the sense organs (i.e., eyes, ears, nose, mouth, and skin) (Weiten, 1998). This ability to perceive and interpret stimulus allows the human being to make meaningful sense of the world and environment around them. However, even as the human being is able to perceive and interpret stimuli information through all sense organs, stimuli is most often or primarily interpreted using the visual (eyes) and auditory (ears) sense organs (Anderson, 2009). However, for the purpose of this paper, the visual information process will be examined.

Secondly, range of similarities and differences are perceived in the sets of rules constraining the language structure of Auslan and English. In comparison to English, sign languages are visual languages, hence it is distinct in modality and word-ordering structure (Damian, 2011). To illustrate, the words of spoken languages are delivered in a fairly linear pattern, both in time and on paper (Bejan, 2001). This linear sentence structure is observed in English, but the same is not demonstrated in Auslan. However, despite this distinction, the order of signs remains of importance to produce meaningful sentences. This is because Auslan conveys many grammatical features found in the English language at phonological, morphological and syntactic levels (Johnston & Schembri, 2007). An individual’s poor English grammar is attributed for sentence fragments. These poorly formed English sentences occur when a sentence lacks a subject, a verb or do not express a complete thought (Schuster, 2006). In the same manner, the wrong ordering of signs will affect the fluency of the language. For instance, the linear English sentence ‘many black cars have disappeared’ will be signed as MANY-BLACK-CAR-DISAPPEAR (Johnston & Schembri, 2007). In this example, it is important that the determiner (MANY) and adjective (BLACK) are situated before the noun (CAR) (Johnston & Schembri, 2007). This is done for the purpose of identifying the noun within the sentence, which subsequently lead to the formation

In experiment 1, participants were instructed to press a key to determine if the stimulus was red, blue, yellow, or green. On the second half of the experiment, the stimulus appeared in grey with only one colored letter which was positioned randomly. Error rates for the experiment were below 2.5% for each condition, which is quite low. Experiment 2 was the same as experiment 1 except that there were 114 data collections instead of 288 and there were 36 practice trials instead of 72. According to experiment 1 and 2 it is suggested that the effect of

Low levels of processing include operations like counting the letters in words and higher levels of processing might include forming semantic relationships such as understanding what the words’ meaning is. According to Craig and Lockhart who formulated this theory memory recall would improve as the information is processed in greater depth. However it has been hard to define exactly what depth is and it has been found that there are other factors that make people remember things. (Zachmeister, E.B., Nyberg 1982)

An interesting challenge arises when a task such as color naming is identified as both controlled and automatic, by varying the other task involved. Color naming is identified as a controlled process when the other task is word reading, but as an automatic process when the other task is shape naming. Cohen, Dunbar and McClelland (1990) proposed an alternative explanation of the Stroop effect, which does not distinguish between automatic and controlled processing. Instead, they proposed that automaticity is a range, and that Stroop interference depends on the relative degree of learning the particular tasks, not on processing speed.

Humans have a unique and wonderful device in how one sees. The eye and brain work together to turn the world into visual data one’s brain can understand and use. There are some eye conditions that inhibit the sight or the recognition of the shapes one sees. Research continues to overcome these conditions as well as to further understand the biochemical reaction that gives humans the sight and understanding one has of visual data. Included in the paper are some of the latest research methods.

Burgess and Hitch (1999) added to and tested the original model of the phonological loop. They created multiple lists: one with the combination of short and long words, one with short words, and one with long words. Burgess and Hitch predicted that the short list would have a higher recall rate, while the long list would take longer to memorize. However, the mixed list would take less time to recall but longer time to memorize (Burgess & Hitch,1999).

Early studies have widely researched attention with selective processing (Driver, 2001). Broadbent (1958) filter theory of attention states that certain information does not require focal attention. It is based on certain stimulus attributes such as colour and shape (Friedenberg, 2012). A previous study carried out by Treisman and Schmidt (1982) proposes that when attention is diverted from a display of several figures, the participants incorrectly combine the features of colour and shape therefore increases the illusory conjunctions portrayed by the participants (Tsal, 1989). Another study by Shaw (1978) found that reaction time of participant to identify targets varied with the probability that a target would appear in a particular display location. These results indicate that different amounts of attention towards the targets are distributed to different positions in the visual field. However, Houck and Hoffman (1986) found that the feature integration of colour and orientation can sometimes be accomplished without attention (James et al.,

This essay will talk about face recognition and several reasons why it has been studied separately. The ability to recognise faces is of huge significance of people’s daily life and differs in important ways from other forms of object recognition (Bruce and Young, 1986). Than this essay will talk about the processes involved in face recognition which comes from the diversity of research about familiar and unfamiliar faces-it includes behavioural studies, studies on brain-damaged patients, and neuroimaging studies. Finally, it will discuss how face recognition differs from the recognition of other object by involving more holistic or configuration processing and different areas of the brain (Eysenck & Keane, 2005).

Word recognition involves an individual’s ability to identify words independently without requiring related words for contextual help. A widely examined topic in the field of cognitive psychology, it deals with understanding printed letters as a word which has been kept in the lexicon. The word frequency effect is important in the recognition of words. It suggests more common words in printed language are easier, faster and more accurate to distinguish than words that appear less frequently. Outlined in their journal article, Howes and Solomon utilized Thorndike-Lorge’s word count for word frequency and measured the threshold of recognition. They found correlation coefficients of -.68 to -.75 between word frequency and threshold or duration.

3. Barry, A. M. S. 1997. Visual intelligence: Perception, image, and manipulation in visual communication, Albany: State University of New York Press.

This buffer was a temporary memory store in which the unselected information could be held in parallel for short periods of time (Styles, 2006). Information can remain in the buffer for processing at a later stage, if this is not the case, it corrodes and is then lost (Martindale, 1991). It is only when the “information passes through the filter into the limited capacity channel, which is a serial processor, that it is identified” (Styles, 2006, p19). The indication is that therefore, selection from the parallel input is made at early levels of processing, and is consequently an “early selection model” (Styles, 2006). A number of theorist’s have, however, introduced models that completely reject Broadbent’s Filter model. An example is that of Deutsch and Deutsch’s attention model (Martindale, 1991).

The Burton, Bruce and Johnston’s (1990) Interactive Activation and Competition (IAC) Model includes: the face recognition unit; the person identity node, the sematic information unit and the name input unit.

Humphreys and Bruce (1989) proposed a model of object recognition that fits a wider context of cognition. According to them, the recognition of objects occurs in a series of stages. First, sensory input is generated, leading to perceptual classification, where the information is compared with previously stored descriptions of objects. Then, the object is recognized and can be semantically classified and subsequently named. This approach is, however, over-simplified. Other theories like Marr and Nishihara’s and Biederman’s

Increasing the number of words isn’t enough because the speech recognition system is unable to differentiate words like ‘to’ and ‘two’ or ‘right’ and ‘write’ (6 ,p.98).