## 4 The Improvement of Tone Pronunciation Ability with Applications
### Application Interface and Operation Design  
Although the perceptual training application was shown to be more effective than the imitation pronunciation practice application, according to the questionnaire results after the experiment, the users of the NHK application focused more on learning and found it harder to learn tones. In addition, the NHK app is more interesting for tone learning, and the perceptual training app users felt that it was more troublesome.  
Therefore, we optimized the interface design, operation design, and loading time, aiming to minimize the extraneous cognitive load without changing the intrinsic cognitive load (contents of learning). The most important optimization for tone recognition is the effort required to answer the perceptual training questions. We eliminated the loading time (0.8 to 1 s in the prototype) required to move to each question, task, and confirmation screen of answer status. The operations of the optimized perceptual training application required to answer the questions are: 1. Click the button to play the sound of the perception question, 2. Click the button to answer the question, 3. Swipe to move to another question. With the perceptual training app after optimization, it was possible to move to the next question within the length of sensory memory (about 1 second) and challenge the next question.  
The results of the experiment showed that the users of the optimized perceptual training app performed 10.6% and 20.1% higher on the two basic pronunciation tasks than they did with the prototype, and in the phrase pronunciation tests, the performances of the optimized perceptual training app users were improved by 12.5%. In the results of the paired sample t-test, there is a statistically significant difference in the correct answer rate of the pronunciation tasks from learning with the prototype and the optimized perceptual training application (\(t(9)=2.36\), \(p=0.043\), [PERSON]'s \(d=0.745\); \(t(9)=2.61\), \(p=0.028\), [PERSON]'s \(d=0.827\); \(t(9)=2.45\), \(p=0.037\), [PERSON]'s \(d=0.766\)) The results of the questionnaire after the experiment (Table 1) show that the appraisal of the app after optimization improved considerably; however, it is slightly lower than the NHK's app.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Average Score/Item**} & \multirow{2}{*}{**NHK App**} & \multicolumn{2}{c}{**Perceptual Training App**} \\ \cline{3-4}  & & **Prototype** & **Optimized** \\ \hline I focus on learning the tone & 5 & 4.2 & 4.8 \\ \hline (At first use) I use the application thoroughly & 5.4 & 4 & 5.2 \\ \hline (At second use) I use the application thoroughly & 5.4 & 4.4 & 5.2 \\ \hline This application helps me to understand tone & 5.4 & 5 & 5 \\ \hline The pronunciation test helps to train tone ability & 5.2 & 5 & 6 \\ \hline Pronunciation tests are interesting & 5.4 & 5.2 & 4.8 \\ \hline Tone learning is interesting with this application & 5.2 & 4.4 & 4.8 \\ \hline The learning method of this application is troublesome & 2.4 & 2.8 & 2.4 \\ \hline Tone perception is difficult & 4.4 & 5 & 4.2 \\ \hline Tone pronunciation is difficult & 4.2 & 5 & 3.8 \\ \hline \hline \end{tabular}
\end{table}
Table 1: The questionnaire result of application users (6-point Likert scale). Japan Broadcasting Corporation (NHK).  
Figure 3: The average correct answer rate and variance of application users on the phrase pronunciation task.