Chapter 4 Results and analysis
4.1 Overall analysis
4.1.2 Frequency and Accuracy rate
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her [55] also reached 90% of stabilization at 1;3. The data of stabilization will be presented later in the last section in this chapter. In subject #4’s data, the four contrastive tones appeared roughly at the same time, and the data in subject #6 could only show that [55] was the first appeared tone in his tonal development.
Second, once children have reached the one-word stage, the four contrastive tones would emerge one after another in a short period of time. Subjects #2, #3, #4, and #5 spent about one to three months to contrast all the citation tones, but it took more than five months for subject #6 to apply all tones in his lexicon. Third, the neutral tone tended to appeared last comparing to the four citation tones. Data showed that the neutral tone was the last emerged tone in subject #2, #4, and #5. Only subject #3 was the exception that her neutral tone was the second appeared tone which showed up later than [51].
4.1.2 Frequency and Accuracy rate
In the previous section, I presented the ordering and ages of tone emergence, and found that the high-level tone [55] and falling tone [51] appeared earlier than [35] and [21], and the neutral tone tended to appear last. Thus, in order to see whether the frequency and accuracy rate of tones would rank in the same sequence as the tone emergence, the number of occurrences and the correctness of each tone would be computed in the section. The tone frequency would inform which tone is more frequently used and which tone is less used. In addition to tone frequency, the accuracy rate is also
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crucial for determining the degree of development. A tone with higher accuracy rate reflects a more mature and more stable degree of acquisition. By analyzing the tone frequency and accuracy rate, the detail of tone acquisition could be better described.
Among the 2062 tokens, there were 588 monosyllabic tokens and 1474 disyllabic tokens, and each of the disyllabic tokens had 2 syllables, so the 1474 disyllabic tokens would have 2948 syllables. Thus, there were totally 3536 syllables (588+1474x2=3536) in the data. As mentioned in chapter 3, the tokens without meaning could also apply frequency analysis. To see which tone was used more frequent, the 3536 syllables would all be included. The four tones were written in the tone values modified from Chao’s (1968) tone number, and the neutral tone was also included in the tone frequency chart with the label of ‘Neut.’
From the total of 3536 syllable tokens, the frequencies of all tones were calculated below and the number of tokens and frequencies were presented in Table 4.4 and Figure 4.1.
Table 4.4 Number of tokens and frequencies of tones in all syllabic tokens
[55] [35] [21] [51] Neut Total
Number of tokens 960 954 894 565 163 3536 Frequencies of tones 27.1% 27.0 % 25.3% 16.0% 4.6%‧
Figure 4.1 Frequencies of tones in all syllabic tokens
In Figure 4.1, the bar graph presented the frequency of each tone. The difference of the five percentages was statistically significant (χ2=18.2, p<.001). The highest three bars, [55], [35], and [21] were all higher than 25%. Falling tone [51] ranked as the fourth place with 16% of appearance, and neutral tone appeared last frequently, accounting for 4.6%.
Actually, it was unfair to compare the neutral tone with other tones in frequency, because in Mandarin, neutral tones only appear in weak stress that are usually in utterance-final position. If children acquire this phonological rule early in this stage, the neutral tone would scarcely be found in utterance-initial positions in monosyllabic and disyllabic tokens. In fact, Figure 4.1 showed that children preferred using [55], [35], and [21] the most, and the neutral tone appeared last frequently. The hypothesis that children learned the phonological rule of neutral tone in this stage might be approved. Then, to see whether the acquisition of tones could demonstrate the rule that ‘practice makes perfect,’
we need to compare the ranking with accuracy rate below.
The accuracy rate was calculated by taking meaningful tokens. Meaningful tokens
27.1% 27.0% 25.3%
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had clear targets which encoded with target tones, so the correctness could then be decided. Among the 3536 syllables, only 2354 tones were syllables that had target tones, so the 2354 syllables were included in the accuracy rate analysis. The accuracy rates were calculated by dividing the number of correct tokens by the number of targeted tones.
Table 4.5 presented the fraction of the accuracy rates in each tone, and the percentage of accuracy rates were shown in Figure 4.2.
Table 4.5 Number of tokens and accuracy rates of tones in all syllabic tokens
[55] [35] [21] [51] Neut
Number of correct tokens
/ number of targeted tones 468/529 586/642 598/703 298/356 91/111 Accuracy rates of tones 88.5% 90.3 % 85.1% 83.7% 82.0%
Figure 4.2 Accuracy rates of tones in all syllabic tokens
The result suggested that all the lexical tones including neutral tone showed high percentages in accuracy rate. The most stable tone was [35] that reached 90% of accuracy rate. The high-level tone [55] showed lower rate than [35], accounting for 88.5%. The third and fourth places were [21] and [51], and the neutral tone was the last. However, the numbers of accuracy rates in all tones were all high, and there was no significant
88.5% 90.3%
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differences found among the five percentages (χ2=5.229, p=0.265). If the accuracy rates were not different statistically, we could only say that the degree of tonal development was similar during the age between 0;10 to 1;6.
Now that the accuracy rate in the overall data could not indicate which tone was more mature and which was not, the following analyses would separate the data into monosyllabic and disyllabic tokens and see whether there would be more specific results in the ordering of tonal acquisition.