# Call Redistribution for a Call Center Based on Speech Emotion Recognition
## 4 Simulation and Experimental Results
From the results presented in Table 5, it can be observed that as the number of simultaneously received calls grows, the calls featuring three recognized emotions considered as indicators of more urgent caller's state, namely fear, anger and sadness, show the tendency to have a decreased waiting time after the proposed call redistribution. On the other hand, the calls featuring recognized neutral speech and joy show tendency of increased waiting time as the number of simultaneously received calls grows, but it is considered justified as long as more urgent calls are processed instead of less urgent one. To examine the results in the case of larger number of iterations, the simulations were performed using 200, 500, and 1000 iterations in all three experimental settings (3, 5, and 7 simultaneously received calls). For each experimental setting, obtained results are presented in Tables 6-8, respectively. Regarding initial average waiting time, even with 1000 iterations there are differences in evaluated initial average waiting time across five emotional states due to combination of random order of emotions in callers' queue and random duration of each call in the queue. Similar to the experiments with 50 iterations, after application of SER and call redistribution, calls featuring fear and anger have achieved significant reduction in waiting time. Unlike the simulation with 50 iterations, calls featuring sadness achieved in some cases slight increase and in some cases slight decrease in waiting time after call redistribution. This can be explained with the fact that neutral callers are put in the middle of callers' priority, so it was expected that their waiting time after increased number of iterations is evaluated as slightly changed initial average value. As can be observed from Tables 6-8, callers recognized as being in neutral and joyful states will have increased waiting time, similar to the results obtained in the simulation with 50 iterations. Experimental results show the decrease in waiting time of the prioritized emotions. Indeed, there is a minor probability of misrecognizing anger as joy (because both are characterized by a high arousal, but opposite valence poles), and placing that caller at the end of the callers' queue, but possible negative effect depends on the position of such a call in original queue and emotional states of other callers in it. Overall experimental results show an essential decrease in waiting time of the prioritized emotions with negative valence. In real-world emergency call centers, it is unlikely to expect all emotions equally distributed, as it was case in our simulation experiments. It is more likely to receive more calls featuring fear and less calls featuring joy, as it is reported for the CEMO corpus recorded in a real-world medical call center [7]. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Emotion** & **3 Calls Simultaneously** & **5 Calls Simultaneously** & **7 Calls Simultaneously** \\ \hline fear & 2:35 & 3:52 & 5:45 \\ anger & 1:18 & 2:39 & 2:22 \\ sadness & 0:15 & 0:53 & 0:52 \\ neutral & \(-\)0:58 & \(-\)1:06 & \(-\)2:37 \\ joy & \(-\)2:11 & \(-\)4:10 & \(-\)5:30 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Waiting time reduction after the proposed call redistribution is applied. Time is expressed in [min]:[s]. the dialogue strategy in a call center, the current call will be ended faster or put on hold, so that an emergency call would be received immediately. Although there are evident differences between the emotional speech corpus recorded in a real call center and the acted emotional speech corpus recorded under controlled conditions, the experimental results in the simulated call center give a promising sign that the proposed approach to SER and call redistribution based on it would improve effectiveness of a real call center service. The proposed algorithm is a basis for detecting critical users in the specific type of call centers considered in the research.