## 4 Evaluation Results and Discussion
### Performance across Session Durations
#### 4.4.1 First Model Group  
Figure 6 compares the QoE models in the first group. It can be seen that the performances of these models are generally low and considerably variable. In particular, the ranges of the PCC, SROCC, and RMSE values are respectively [0.29, 0.93], [0.25, 0.90], and [0.35, 1.02] for _[PERSON]'s_ (_ori_) model, [0.29, 0.81], [0.21, 0.83], and [0.42, 1.02] for _[PERSON]'s_ (_mod_) model, [0.06, 0.78], [0.11, 0.84], and [0.55, 1.03] for _[PERSON]'s_ model, and [0.07, 0.72], [0.07, 0.79], and [0.57, 1.02] for the _[PERSON]'s_ model. With respect to the _[PERSON]'s_ (_ori_) model, this model yields high performance on the _W-SQoE-I_ (PCC = 0.93) and _W-SQoE-II_ (PCC = 0.81) databases, which contain short sessions (8-s and 10-s). By contrast, its performance is generally low on the other databases with longer session durations (PCC \(\leq\) 0.73, SROCC \(\leq\) 0.81, RMSE \(\geq\) 0.57). It can be explained that this model is originally developed using short sessions (i.e., 5-15 s), and so not effective for longer sessions. In particular, it performs poorly on the databases including stalling events such as _VL04_, _VLDB_, and _VL13_ (i.e., PCC \(\leq\) 0.44, SROCC \(\leq\) 0.55, RMSE \(\geq\) 0.85). This is due to the fact that the model does consider the impact of stalling events. This result suggests that the model built based on short sessions such as _[PERSON]'s_ may not be effective for medium and long sessions. In addition, the impact of stalling events is crucial to be considered in QoE models. From Figure 6, it can be seen that the performance of _[PERSON]'s_ model on the _W-SQoE-I_, _TR04f_, _TR04p_, and _VLDB_ databases is acceptable and significantly higher than those of the other databases. In particular, its PCC and SROCC values are in the range from 0.74 to 0.84 while its RMSE values are from 0.58 to 0.62. This result can be explained as follows. The _[PERSON]'s_ model mainly focuses on quantifying the impact of stalling events by means of various inputs such as the total number of stalling vents and the maximum of stalling durations. Meanwhile, only one input of QP average is used to model the impact  
Figure 6: Performance of _[PERSON]’s_, _[PERSON]’s_, and _[PERSON]’s_ models in the first group over the test databases. (a) PCC; (b) SROCC; (c) RMSE. of quality variations. However, this input is obviously not able to distinguish quality switches with different amplitudes [40]. Meanwhile, it is well-known that abrupt switches commonly cause more negative influence than smooth ones [40]. Thus, as a consequence, this model performs well on the four above databases that contain a major number of sessions with stalling events. Meanwhile, for the _W-SQoE-II_, _VLCQ_, and _TRCQ_ databases that contain only quality variations, the _[PERSON]'s_ model results in very low performance (i.e., PCC \(\leq\) 0.65, SROCC \(\leq\) 0.57, and RMSE \(\geq\) 0.55). This shows that the use of only QP average is not sufficient to model the impact of quality variations. In comparison to the _[PERSON]'s_ model, the _[PERSON]'s_ model is noticeably the worst on databases containing sessions with frequent stalling events such as _W-SQoE-I_, _TR04f_, _TR04p_, and _VLDB_. This is probably because the _Yin's_ model simply uses the total stalling durations to quantify the impact of stalling events. Meanwhile, for the _VL04_, _VL13_, and _VLCQ_ databases, the performance of the _[PERSON]'s_ model is substantially higher. Note that, in the three databases, most or all of the sessions do not include stalling events. This implies that the use of the bitrate average and the average of switching amplitudes as in the _[PERSON]'s_ model is more effective than the QP average in representing the quality variations. Still, the performance of the _Yin's_ model is not very high. In particular, the PCC and SROCC values are less than 0.80 and the RMSE values are higher than 0.57. These results suggest that the use of the sum of stalling durations only is not able to fully represent stalling events appearing in streaming sessions.