# Perceptual Quality of Audio-Visual Content with Common Video and Audio Degradations
## 6 Perceptual Experiment 1 (Video-Only)  
In this first experiment, volunteers were presented with a set of audio-visual video clips, and they were asked to rate them based on their perceived quality and content. Three types of distortions were added to these video clips: compression distortions generated by coding the videos at different bitrate levels (and codec algorithms), packet losses transmission distortions generated by deleting video bitstream packets, and frame-freezing transmission distortions generated by deleting and repeating frames. Distortions affected only the video  
Figure 4: ACR Quality and Content scales. component; meanwhile, the audio component remained untouched. The experiment focused on analysing the impact of visual distortions on the perceived audio-visual quality. Sixty (60) source stimuli (out of the 140 stimuli pool described in Section 5) were considered for the experiment. Their video components were processed, generating PVSs with different types of visual impairments. The PVSs were organized in a group of ten (10) different HRCs, as described in Table 7, with no HRC having simultaneously packet-loss and frame-freezing distortions. For this reason, two test scenarios were considered for Experiment 1: a coding-packetloss scenario (HRC1 to HRC5) and a coding-freezing scenario (HRC6 to HRC10). In order to help participants recognize the range of quality in the experiment, two anchor (ANC) conditions were included. These ANCs corresponded to video clips compressed at extremely high bitrate levels, with no packet-loss or frame freezing distortions. These twelve (12) test conditions (10 HRCs plus 2 ANCs) were replicated for all sixty (60) source stimuli, resulting in seven hundred and twenty (720) test stimuli. As mentioned before, for each experimental session, participants saw the content corresponding to each original sequence only once. That is, each participant was presented with only 60 test stimuli, out of the 720 available, all corresponding to different source contents. These 720 sequences compound the first part of the UnB-AV dataset [47]. The sub-set is labelled as UnB-AV-Experiment-1, and it is available for download along with the entire UnB-AV dataset. Figure 5 presents the quality scores given by participants for each of the HRCs. For each HRC, the \(\text{MQS}_{\text{HRC}}\) value is represented by the larger dot in the middle. It can be observed that for most test conditions, the responses are consistent, i.e., the spread of points is small. Moreover, test conditions with higher quality scores (e.g., ANC1, ANC2, and HRC10) presented a higher agreement among participants. In general, it can be observed that participants used the entire scale presented to them (1 to 5). Figure 6a,b shows the Mean Quality Score (\(\text{MQS}_{\text{HRC}}\)) and Mean Content Score (\(\text{MCS}_{\text{HRC}}\)), respectively, for Experiment 1. For each HRC, a confidence interval of 95% is included, plus all HRCs are grouped according to Frame-Freezing and Packet-Loss degradations. A combination of a bitrate value (BR) plus a packet-loss ratio (PLR) or frame-freezing configuration (number, length and position) is assigned to each HRC (see Table 7). The \(\text{MQS}_{\text{HRC}}\) values (presented in Figure 6a) fell between 1.92 and 4.5, with no evidence of a scale saturation. As expected, \(\text{MQS}_{\text{HRC}}\) increases with the strength of the bitrate, packet-loss, and frame-freezing degradations. That is, participants were able to distinguish between different degradation levels inserted in the visual component.