Quality of Experience

In this chapter, we provide a motivation for the upcoming chapters of the book. We discuss how the concept of Quality of Experience (QoE) has evolved during the last decades, resulting in a need for a common terminology, as well as the need for applying the identified concepts to new applications and services. The first issue was already addressed by the “Qualinet White Paper on Definitions of Quality of Experience”, the history of which will be briefly reviewed, but due to its very nature that White Paper could not cover all concepts, applications and methods in sufficient depth in order to be helpful for scientists and practitioners alike. We hope to overcome this limitation with the present book, and present an outline of the contents and the relationships between individual chapters.

The chapter discusses the processes of human perception and experiencing, and of quality formation. In this context, definitions of relevant terms are re-visited and adapted to the presented, updated view, and different aspects of research into quality at large and into Quality of Experience are summarized. Using a conceptual model, the quality formation process is analyzed in view of different contexts and tasks, such as taking part in a quality test under controlled conditions, experiencing a video presentation or concert, or exploring a system or device when considering a purchase in a shop. We provide a short overview of different quality assessment methods, and outline related trends in QoE research.

The current chapter discusses the concepts Quality of Experience and User Experience. As Quality of Experience is introduced in the previous chapter, this chapter starts with an introduction to the User Experience concept at the level of theory and practice. First its origins, definitions, and key attributes are discussed. This is followed by an overview of methods and approaches to evaluate User Experience in practice. Thereupon, we discuss both concepts in comparison. While a number of similarities are identified, these are exceeded by the number of differences, which are situated at the theoretical-conceptual level and the methodological-practical level. It is concluded that User Experience is the more mature concept, both at the level of theory and practice. Thus the literature within the User Experience domain can be of great value for the Quality of Experience-community, especially if the latter intends to really put the recently proposed more holistic definition of Quality of Experience into practice.

In this chapter different factors that may influence Quality of Experience (QoE) in the context of media consumption, networked services, and other electronic communication services and applications, are discussed. QoE can be subject to a range of complex and strongly interrelated factors, falling into three categories: human, system and context influence factors (IFs). With respect to Human IFs, we discuss variant and stable factors that may potentially bear an influence on QoE, either for low-level (bottom-up) or higher-level (top-down) cognitive processing. System IFs are classified into four distinct categories, namely content-, media-, network- and device-related IFs. Finally, the broad category of possible Context IFs is decomposed into factors linked to the physical, temporal, social, economic, task and technical information context. The overview given here illustrates the complexity of QoE and the broad range of aspects that potentially have a major influence on it.

It is often the case that in the current literature, the term “QoE” is used in contexts where “QoS” would be more appropriate. This is likely due to several reasons, one of which being the current popularity of all things related with QoE, but more fundamentally it is due to the boundaries between QoS and QoE not being clearly defined—and indeed, sometimes hard to define clearly. QoE is an intrinsically multi-disciplinary field, and practitioners from different backgrounds see it, quite naturally, from different perspectives colored by their own expertise. For networking people, in particular, QoE is sometimes seen as a simple extension, or even a re-branding, of the well-established concept of QoS. In this chapter we will delve into the differences and commonalities between the two, with the goal of easing and encouraging their proper use.

The current paradigm change towards Quality of Experience (QoE) does not only have conceptual and methodological consequences, but at the same time exhibits a profound impact on corresponding economic and business models, especially in the telecommunications market. This chapter deals with related issues from several layers of abstraction. We consider the general ecosystem level, proceed to resulting Customer Experience Management (CEM) systems, discuss consequences for Service Level Agreements (SLA), and finally analyze the implications if it comes to charging for QoE. As a result, it should become clear that integrating the economic dimension into QoE research provides an indispensable step towards enabling the future commercial success of the telco industry as such.

This chapter outlines common brain activity correlates that are known from neuroscience, gives an overview on established electrophysiological analysis methods and on the background of electroencephalography (EEG). After that an overview on study designs will be given and a practical guideline for the design of experiments using EEG in the research area of Quality of Experience (QoE) will be presented. At the end of this chapter we will close with a summary, give practical advice, and we will outline potential interesting future research topics.

This chapter gives an overview for Quality of Experience (QoE) practitioners on common setups in emotion research using audio (sounds), visual (pictures) and audiovisual (video clips) stimulus material to induce emotions. After presenting available databases for the different modalities, methods for subsequent as well as continuous self-assessment are discussed. Next to self-assessment, analysis of accompanying physiological changes is a common means to evaluate emotional responses. Here, typical measures of peripheral physiology are summarized. Finally, practical advices for including material with emotional content and recording physiological signals in experiments on audiovisual quality are given, and future research directions are outlined.

Most research on Quality of Experience treats QoE as a static event. As a result, QoE is measured for stimuli of delimited length, and the QoE which is associated with the stimulus is considered to be stable along its duration. However, this rarely happens in reality where usage episodes extend over several seconds and minutes (e.g. a phone call), hours (e.g. a video film), or regularly over periods of weeks or months (when considering QoE of a subscribed service). In this chapter, we will discuss the cognitive processes involved when QoE is integrated over usage episodes, and describe corresponding assessment methods. We will also review models for estimating episodic and multi-episodic QoE from momentary QoE judgments or their predictions.

This chapter discusses the relation between interactivity and QoE. In this context, a definition of interactivity comprising human-to-human interaction as well as human-to-machine interaction is presented, and a description of a possible instrumentation is given. In terms of quality formation, a mediation layer between quality influence factors and perceived quality features is introduced that allows the inclusion of interactivity-related perception in the quality formation process. A discussion of commonalities and differences between interaction with a system and interaction with one or several other persons via a system identifies the open challenges for reliable and successful measurement of interactivity related aspects and the identification of relationships between these interaction measures and QoE.

The goal of any speech service is the transmission and/or processing of speech signals. In this chapter we discuss the Quality of Experience (QoE) of speech communication systems, including networks, speech processing applications and terminals. We then give an overview of the methods employed to quantify and further estimate the QoE of speech communication services with a focus on diagnostic instrumental models. Such models provide indications on either the technical causes of degradations or the quality features impacted by a component in the speech communication system.

In this chapter, we will address the quality experienced when listening to speech which is synthesized by state-of-the-art synthesis systems which generate artificial speech from text. Such systems are used, e.g., in information and navigation systems, but also for generating audiobooks. We describe both, auditory evaluation methods as well as instrumental models predicting perceived QoE. Besides overall perceived quality, we focus on perceptual quality features that can be used for diagnosis and system optimization.

Audiovisual communication has expanded rapidly over the last years on computers and mobile devices. This chapter discusses the key aspects of Quality of Experience of the audiovisual communication. We will give an introduction to audiovisual communication and explain technical elements and perceptual features which relate to the Quality of Experience. Main subjective and instrumental quality assessment methods will be presented. Finally, we specifically discuss a few key aspects impacting quality, namely, time-varying quality perception, audiovisual quality integration as well as the impact of overall delay and audiovisual synchrony, and give an outlook for future work.

With today’s technical possibilities, in particular, packet-based data transmission and high processing power, telephone and videoconferencing systems celebrate increasing interest. However, the success of such systems is essentially determined by the quality provided and experienced when using them. This is why a high need of appropriate assessment methods can currently be observed. Given the broad range of possible solutions, assessing QoE of so-called telemeetings becomes very difficult and brings along the need for a high degree of variability regarding assessment methods. Since multiple participants usually communicate via such systems, it is required to also investigate aspects of the interaction process and their influence on QoE. Furthermore, the multiparty situation enables users to directly perceive asymmetries in the equipment and in qualities provided from different sites, which affects the perceptual situation as well. This chapter is intended to explain the described challenges in detail and to give first insights into how they might be handled.

Audio with good quality is the essential fundament for all multi-media services. The transmission of audio signals relies on efficient encoding and decoding algorithms (codecs) that enable the reduction of the required channel capacity, but still provide an excellent audio quality, even when transmission errors occur. The most succesfull audio codecs are mp2, mp3, aac and ac3. The codecs employ sophisticated signal processing algorithms imitating properties of hearing. The processing may cause specific artifacts such as high frequency loss, narrow-band noise and pre-echoes. The final quality needs to be verified with statistically valid listening tests. Detailed procedures for conducting reliable speech and audio tests are defined in ITU Recommendations P.800, BS.1116, and BS.1534. Instrumental measurement methods such as BS.1387 replicate subjective tests allowing the estimation of the perceived quality. The ITU Recommendation P.1201 is a recently standardized method for estimating the audio quality of a transmitted signal without the need to have a reference signal available.

Complementary to non-spatialized signals and their transmission, this chapter gives an overview of the quality of rendering methods that create spatial sound. Common methods and the underlying concept of a virtual sound scene are introduced and the herewith associated quality features. In particular, evaluation strategies and experimental results are presented in order to discuss spatial and timbral quality features of spatial audio rendering.

Haptic communications refers to the ability to touch, feel and to physically manipulate objects in a remote (real or virtual) environment via technical means. The realization of convincing haptic interactions requires a solid understanding of both kinesthetic and tactile perceptual mechanisms and stimulation principles. This chapter starts with a concise overview of the current state of knowledge in these two areas. Then, we discuss the main performance parameters for haptic interaction systems, and point towards factors that may influence QoE in haptics. So far, the quality experienced by the human during haptic interaction has been mainly evaluated via time-consuming and costly subjective tests and only recently, first preliminary approaches for objective quality evaluation have surfaced. We briefly touch upon this topic and finish the chapter with a discussion of model-based prediction of haptic feedback quality.

This chapter addresses QoE in the context of video streaming services. Both reliable and unreliable transport mechanisms are covered. An overview of video quality models is provided for each case, with a focus on standardized models. The degradations typically occurring in video streaming services, and which should be covered by the models, are also described. In addition, the chapter presents the results of various studies conducted to fill the gap between the existing video quality models and the estimation of QoE in the context of video streaming services. These studies include work on audiovisual quality modeling, field testing, and on the user impact. The chapter finishes with a discussion on the open issues related to QoE.

3D video has been considered as the next step in television for some time. The transition from 2D to 3D is frequently seen as comparable to the transition from monochrome to color. The introduction of this new dimension adds new challenges regarding the question of its relates with Quality of Experience (QoE). This chapter mainly focuses on presenting the particular challenges related with stereoscopic 3D video quality. This includes the difficulty to evaluate QoE of 3D video, taking into account all relevant factors. In particular, traditional approaches fail to capture aspects such as the added value in terms of QoE due to 3D depth or quality-issues brought by 3D-specific artifacts and their effect on visual comfort, so that alternative solutions for evaluation are required. As a consequence, the aim of this chapter is to address 3D-specific aspects of visual perception. The employed technology is another aspect of high influence on 3D video QoE. The chapter addresses the different issues related with content creation, transmission and representation, to help the reader understand the differences to a 2D transmission chain, and how technology affects the perception and the construction of the general judgment of 3D video QoE.

Crowdsourcing enables new possibilities for QoE evaluation by moving the evaluation task from the traditional laboratory environment into the Internet, allowing researchers to easily access a global pool of subjects for the evaluation task. This makes it not only possible to include a more diverse population and real-life environments into the evaluation, but also reduces the turn-around time and increases the number of subjects participating in an evaluation campaign significantly by circumventing bottle-necks in traditional laboratory setup. In order to utilise these advantages, the differences between laboratory-based and crowd-based QoE evaluation must be considered and we therefore discuss both these differences and their impact on the QoE evaluation in this chapter.

The Chapter provides an overview of Quality of Experience research for web-browsing, highlighting recent research trends. It indicates how Web-QoE assessment has evolved from the mapping of technically measured page-load times to quality estimates to the notion of perceived page-load time. Here, the consideration of the user’s current task and respective role of individual element load times is discussed. The interactive nature of web-browsing is further analyzed in terms of temporal effects regarding the subsequent page access of users during typical browsing sessions. Finally, the chapter provides an outlook on future challenges related with the increasing complexity of web-services and respective page-loading processes.

This chapter gives an overview on basic concepts and current research in mobile human–computer interaction (HCI) by showing where it extends the notion of interaction with stationary devices. Important differences next to basic hardware properties (size etc.) are that the corresponding devices offer instant access to the internet and are used in a variety of situations or contexts, where location information so far appears to be the primary way to assess this context. As a consequence, a couple of new research paradigms for field testing emerged, which are structured along the dimensions of scalability (number of users) and research outcomes. The majority of these studies appears to be rather exploratory, less explanatory at the moment. Possible reasons as well as future research directions are discussed.

This chapter introduces the concept of Sensory Experience which aims to define the Quality of Experience (QoE) going beyond audio-visual content. In particular, we show how to utilize sensory effects such as ambient light, scent, wind, or vibration as additional dimensions contributing to the quality of the user experience. Therefore, we utilize a standardized representation format for sensory effects that are attached to traditional multimedia resources such as audio, video, and image contents. Sensory effects are rendered on special devices (e.g., fans, lights, motion chair, scent emitter) in synchronization with the traditional multimedia resources and shall stimulate also other senses than hearing and seeing with the intention to increase the Quality of Experience (QoE), in this context referred to as Sensory Experience.

Playing is the first activity newborn humans immerse themselves in besides fulfilling basic needs. There is no ultimate goal to be achieved: Playing is a process that is only kept alive by the player’s experience of it. This chapter provides an overview over existing concepts and current research on the experience of playing video games. It does so by taking the perspective of a quality engineer, who identifies influencing factors, quantifies them in terms of performance metrics, and analyzes their impact on perceived quality features. To support the development of empirical test methods as well as instrumental prediction models for video gaming QoE, the concepts are grouped in a taxonomy. The chapter is concluded by a discussion of the empirical application of the framework in experiments, a brief look at an existing QoE prediction model, and an outlook at promising future research directions.

This chapter proposes a definition of Quality of Experience (QoE) in the case of task based applications. The definition is followed by the describing of the current work in the field of the QoE methodology in the specific case of a security system. Different metrics predicting QoE proposed in the literature are discussed.

Over the top services so far discussed in this book, such as speech and video telephony, gain the attention of mobile users, who nowadays do not expect the connectivity only, but also demand for Quality of Experience (QoE). In this sense, the concept of an “always best connected” mobile user faces new challenges. Nomadic use of services and heterogeneity of technology make it impossible to constantly provide the highest transmission quality. As a matter of fact, intelligent management of quality is required and to be successfully in doing so, QoE in heterogeneous networks must be explored and user perception of changing quality must be understood. This chapter addresses user perception of quality while using speech and video telephony in heterogeneous wireless networks. It is in particular focused on user perception of quality changes due to switching between networks, codecs, and encoding bit rates during an ongoing transmission. This knowledge is inevitable for a perception-based design of service and mobility management in modern networks.

This chapter presents an overview of a set of recently proposed QoE-based management approaches that all try so resolve a central dilemma: maximizing user satisfaction while at the same time maximizing resource efficiency and economy. To this end, it first builds bridges between recent approaches towards QoE-based Network Management and standardized Network Management functions. This is contrasted by a discussion of recent approaches towards QoE-based Application Management. Further, it is shown how both Network Management and Application Management can work together in concert. Finally, open issues regarding a better integration of management and QoE are outlined.