Quality and Quality of Experience

Raake, Alexander; Egger, Sebastian

doi:10.1007/978-3-319-02681-7_2

Cited by 100 publications

(82 citation statements)

References 45 publications

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“…Perceptual references are considered to be part of the early perception stage of the quality formation process [57], exerting an influence on attentional and memory-related processing. The subcomponents of the P300, P3a and P3b, were chosen as neurophysiological indicators of these early quality-related processes (see Fig.…”

Section: Discussionmentioning

confidence: 99%

“…It was assumed that the abrupt presentation of an oddball (T, D) would cause an orienting response, which in case of T would be succeeded by memory Fig. 1 Simplified model of quality perception (circles internal processes; parallel horizontal lines internal representations; rectangles input signals, output), based on a conceptual model of internal quality formation [57] and a model of cognitive P300 activity [51] operations. After T, both P3a and P3b waveforms should be triggered, producing the superposed P300 waveform.…”

Section: Experimental Design and Hypothesesmentioning

confidence: 99%

“…1 provided the theoretical framework for the present study, combining a model of internal quality formation [57] with a model of cognitive P300 activity [50,51]. As the three-stimulus oddball paradigm requires the perceptual discrimination of stimuli, triggering of the P3a and P3b was anticipated during the early perception stage of the quality formation process.…”

Section: Introductionmentioning

confidence: 99%

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Perceptual references for independent dimensions of speech quality as measured by electroencephalography

et al. 2017

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Quality of transmitted speech can be decomposed into three perceptual dimensions: Noisiness, coloration and discontinuity (Wältermann, Dimension-based quality modeling of transmitted speech. Springer, Berlin. doi:10.1007Berlin. doi:10. /978-3-642-35019-1, 2013. The purpose of the present study was to explore whether degradation of speech quality on each perceptual dimension affected the morphological and temporal characteristics of the P300 eventrelated brain potential (ERP) component. The P300 is composed of two subcomponents, P3a and P3b, which served as neurophysiological indicators of distinct processes in human quality perception (Polich, Neuropsychology of P300. Oxford University Press, Oxford. doi:10. 1093/oxfordhb/9780195374148.013.0089, 2012; Raake and Egger, Quality and quality of experience. Springer International Publishing, Cham, pp. 11-33, 2014): While the earlier P3a reflects attentional processing after the occurrence of novel sensory events, the later P3b is associated with memory operations following the detection of task-relevant stimuli. Electroencephalography (EEG) was used to record the electrical brain activity of subjects (N ¼ 24) performing a three-stimulus oddball task. Degraded stimuli were generated from the audio recording of a spoken word. The analysis of P3a-and P3b-related activity at electrode positions Fz, Cz and Pz provided support for the existence of different perceptual references for quality-impaired vs. high-quality stimulus contexts as well as quality degradations on single perceptual dimensions.

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Section: Discussionmentioning

confidence: 99%

Section: Experimental Design and Hypothesesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Perceptual references for independent dimensions of speech quality as measured by electroencephalography

et al. 2017

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“…In this context, the concept of QoE appeared to improve this correlation, and its most recent definition is: "QoE is the degree of delight or annoyance of a person whose experience involves an application, service, or system. It results from the person's evaluation of the fulfillment of his or her expectations and needs with respect to the utility and/or enjoyment in the light of the person's context, personality and current state" [41].…”

Section: Relation Between the Dash Standard And The Ifs On Qualitymentioning

confidence: 99%

Video Quality Metric for Streaming Service Using DASH Standard

Rodríguez

Rosa

Alfaia

et al. 2016

IEEE Trans. on Broadcast.

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Currently, dynamic adaptive streaming over HTTP (DASH) standard is used to change the video resolution according to the network capacity of the end user's. However, if the video resolution changes frequently, the attention of the users can be affected decreasing their quality-of-experience (QoE). In this context, this paper proposes a no-reference video quality metric that takes three impairment factors into account, initial buffering delay, temporal interruptions or pauses, and video resolution changes during a video transmission. Also, the temporal locations of pauses and resolution changes are considered. In order to perform this task, extensive subjective tests were conducted. Experimental results show that the evaluators' QoE is highly correlated with the frequency of pauses, video resolution changes and initial delay. Based on these results a video streaming quality metric for DASH services (VsQM DASH ) is formulated and implemented on PC and mobile hand-held devices. Finally, the performance of VsQM DASH is validated with additional subjective tests reaching a person correlation coefficient of 0.99. Furthermore, experimental results demonstrated that the proposed metric has low complexity because it is based on application level parameters and its energy consumption is negligible in relation to the energy consumed by the video player; therefore, can be easily implemented in consumer electronic devices.

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“…Mean Opinion Score (MOS) is a known quantitative metric usually scaled ordinal between 5 and 1 (excellent, good, fair, bad, poor) that subjects assign to their opinion (ITU-T 2003) to measure Quality of Experience (QoE). Raake and Egger (2014) define QoE as the degree of delight or annoyance of a user, who experiences a software product, service or system. QoE results from the evaluation of the user whether his or her expectations are fulfilled in the light of the user context and personality.…”

Section: Background and Related Workmentioning

confidence: 99%

The effect of requests for user feedback on Quality of Experience

2017

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Companies are interested in knowing how users experience and perceive their products. Quality of Experience (QoE) is a measurement that is used to assess the degree of delight or annoyance in experiencing a software product. To assess QoE, we have used a feedback tool integrated into a software product to ask users about their QoE ratings and to obtain information about their rationales for good or bad QoEs. It is known that requests for feedback may disturb users; however, little is known about the subjective reasoning behind this disturbance or about whether this disturbance negatively affects the QoE of the software product for which the feedback is sought. In this paper, we present a mixed qualitativequantitative study with 35 subjects that explore the relationship between feedback requests and QoE. The subjects experienced a requirement-modeling mobile product, which was integrated with a feedback tool. During and at the end of the experience, we collected the users' perceptions of the product and the feedback requests. Based on the users' rational for being disturbed by the feedback requests, such as Bearly feedback,^Binterruptive requests,^Bfrequent requests,^and Bapparently inappropriate content,^we modeled feedback requests. The model defines feedback requests using a set of five-tuple variables: Btask,^Btiming^of the task for issuing the feedback requests, user's Bexpertise-phase^with the product, the Bfrequency^of feedback requests about the task, and the Bcontent^of the feedback request. Configuration of these parameters might drive the participants' perceived disturbances. We also found that the disturbances generated by triggering user feedback requests have negligible impacts on the Software Qual J

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Quality and Quality of Experience

Cited by 100 publications

References 45 publications

Perceptual references for independent dimensions of speech quality as measured by electroencephalography

Perceptual references for independent dimensions of speech quality as measured by electroencephalography

Video Quality Metric for Streaming Service Using DASH Standard

The effect of requests for user feedback on Quality of Experience

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