Between Tasks

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reading test was the least (N=78). It seems that test 3 and 4 induced apparently more speech errors than test 1 and 2. It appears that when visual color began to compete with literal information, subjects might produce more speech errors than just naming or reading. Even though phonological effect emerges only in test 1 and test 4, we still could not ensure whether subjects might induce more errors to the trials with more of less phonological similarity. With regard to Error N, we could not find out any tendency that subjects would produce errors with high phonological similarity because the computed statistics in table 4-2 did not show significant difference in Error N among the four tests. Phonological similarity did not induce a clear phonological effect when subjects produced speech errors. On the other hand, the statistics on RT within the four tests still could not show that trials with high or low phonological similarity would lead subjects to have apparent difference in processing speed. The above results reveal a fact that subjects would not have a consistent response and error patterns when phonological factor was controlled in certain task. It seems that phonological information might not be the only factor to be processed during lexical encoding.

4.2.2 Between Tasks

If we take the four tasks into consideration at the same time, according to the computed results in table 4-3, 4-5, and 4-8, we could see that, the controlled factor caused subjects to reacted differently to trials with phonological similarity (Trial F and RT), as well as their error production (Error N) when we cross-compared the four tasks. There would be different phonological dependency according to the visual task to which they were assigned.

With regard to the Trial F, Error N, and RT among the four tasks, phonological factor seems to induce effect when subjects were under different visual tasks. Even

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though there is less phonological effect within each test, the effect appears more when the four tasks are compared. If we compared either naming or reading test to Stroop naming or homophonous naming test, subjects showed different Trial F distribution between each pair. The result implies that if the literal information interfered in naming mechanism, subjects showed more phonological effect than just naming or reading terms. The possible reason could be that naming or reading reflects more close to facts in our lexical process in life, the effects from individual linguistic levels could be balanced. The effects from linguistic levels would still be balanced in Stroop naming and homophonous naming, but their entire strength of phonological effect in lexical network might be higher than the strength in naming or reading task, which could serve as a reason to explain why phonological effects exists when we crossed-compared the results for these tasks. With a view to the network strength, as shown in figure 2-6 (Dell & O’Seaghdha, 1991), connectionism provides an extended explanation that Stroop technique brings more than one extra signals, literal signal and visual color signal here, into the lexical network. The simulated process of such lexical network is depicted in figure 4-1.

(a)

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(c)

(d)

Figure 4-1. Simulated lexical network for Stroop technique

Compared with naming or reading process in figure 2-6, the simulated processes in figure 4-1 were provided to depict the activation strength in the lexical network when subjects were assigned to take task 3 and 4. The process (a) and (b) indicate the Stroop naming task, with high or low phonological similarity in trials respectively, while (c) and (d) simulated the process of homophonous naming task. The entire network strength is the greatest in (a). The visual color and term are both color concepts, so they got dual semantic activations from the two channels. Even though subjects were told to name the colors, the activation from literal term still existed, which could wrongly attract subjects to read the term and produced speech errors.

Process (b) shows if activations come from dual visual sources with low phonological similarity, the strength of phonological layer would get decreased, and the strength of semantic retained for both of them were colors. The strength of whole network

Literal term: 皇 / x w ɑ ŋ 35 /

Visual color: 洪 / x o ŋ 35 /

semantic lexicon Phonology (High)

Literal term: 皇 / x w ɑ ŋ 35 /

Visual color: 綠 / l y 51 /

semantic lexicon Phonology (Low)

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became less than (a). Homophonous naming test reduced the strength in semantic layer because the literal term and visual color did not belong to the same semantic field. However, the strength of activation in phonological layer retained strong because of high phonological similarity between the dual concepts. The strength in phonological layer as well as in semantic layer might get declined when the dual concepts showed little phonological similarity, as depicted in process (d).

According to above statistic results, process (a) and (b) did not show significant difference in network strength, and process (c) and (d) did not, either. It seems that reduced strength of phonological layer would not be significant, so there was nearly little phonological effect within each visual task. However, if we compared the network in naming or reading task to Stroop naming or homophonous naming task, the strength in network appears significant difference. The effect of phonological strength might get greater when visual competition came up, as in (a), (b), (c), and (d).

The dual activations through visual channel at the same time caused phonological effect to be greater than task 1 and 2, and it also led subjects to produce rather more speech errors in task 3 and 4. It could help us explain why phonological effect induced significant difference in Trial F, Error N, and RT between tasks. The extra strength from more than one input could cause entire activation strength to be more enhanced and confused for subjects than the strength from single input.