16th Sound and Music Computing Conference SMC 2019 (28–31 May 2019, Malaga, Spain)

The 16th Sound and Music Computing Conference (SMC 2019) took place in Malaga, Spain, 28-31 May 2019 and it was organized by the Application of Information and Communication Technologies Research group (ATIC) of the University of Malaga (UMA). The SMC 2019 associated Summer School took place 25-28 May 2019. The First International Day of Women in Inclusive Engineering, Sound and Music Computing Research (WiSMC 2019) took place on 28 May 2019. The SMC 2019 TOPICS OF INTEREST included a wide selection of topics related to acoustics, psychoacoustics, music, technology for music, audio analysis, musicology, sonification, music games, machine learning, serious games, immersive audio, sound synthesis, etc

Robust Modeling of Epistemic Mental States and Their Applications in Assistive Technology

This dissertation presents the design and implementation of EmoAssist: Emotion-Enabled Assistive Tool to Enhance Dyadic Conversation for the Blind . The key functionalities of the system are to recognize behavioral expressions and to predict 3-D affective dimensions from visual cues and to provide audio feedback to the visually impaired in a natural environment. Prior to describing the EmoAssist, this dissertation identifies and advances research challenges in the analysis of the facial features and their temporal dynamics with Epistemic Mental States in dyadic conversation. A number of statistical analyses and simulations were performed to get the answer of important research questions about the complex interplay between facial features and mental states. It was found that the non-linear relations are mostly prevalent rather than the linear ones. Further, the portable prototype of assistive technology that can aid blind individual to understand his/her interlocutor\u27s mental states has been designed based on the analysis. A number of challenges related to the system, communication protocols, error-free tracking of face and robust modeling of behavioral expressions /affective dimensions were addressed to make the EmoAssist effective in a real world scenario. In addition, orientation-sensor information from the phone was used to correct image alignment to improve the robustness in real life deployment. It was observed that the EmoAssist can predict affective dimensions with acceptable accuracy (Maximum Correlation-Coefficient for valence: 0.76, arousal: 0.78, and dominance: 0.76) in natural conversation. The overall minimum and maximum response-times are (64.61 milliseconds) and (128.22 milliseconds), respectively. The integration of sensor information for correcting the orientation has helped in significant improvement (16% in average) of accuracy in recognizing behavioral expressions. A user study with ten blind people shows that the EmoAssist is highly acceptable to them (Average acceptability rating using Likert: 6.0 where 1 and 7 are the lowest and highest possible ratings, respectively) in social interaction

Video Quality Prediction for Video over Wireless Access Networks (UMTS and WLAN)

Transmission of video content over wireless access networks (in particular, Wireless Local Area Networks (WLAN) and Third Generation Universal Mobile Telecommunication System (3G UMTS)) is growing exponentially and gaining popularity, and is predicted to expose new revenue streams for mobile network operators. However, the success of these video applications over wireless access networks very much depend on meeting the user’s Quality of Service (QoS) requirements. Thus, it is highly desirable to be able to predict and, if appropriate, to control video quality to meet user’s QoS requirements. Video quality is affected by distortions caused by the encoder and the wireless access network. The impact of these distortions is content dependent, but this feature has not been widely used in existing video quality prediction models. The main aim of the project is the development of novel and efficient models for video quality prediction in a non-intrusive way for low bitrate and resolution videos and to demonstrate their application in QoS-driven adaptation schemes for mobile video streaming applications. This led to five main contributions of the thesis as follows:(1) A thorough understanding of the relationships between video quality, wireless access network (UMTS and WLAN) parameters (e.g. packet/block loss, mean burst length and link bandwidth), encoder parameters (e.g. sender bitrate, frame rate) and content type is provided. An understanding of the relationships and interactions between them and their impact on video quality is important as it provides a basis for the development of non-intrusive video quality prediction models.(2) A new content classification method was proposed based on statistical tools as content type was found to be the most important parameter. (3) Efficient regression-based and artificial neural network-based learning models were developed for video quality prediction over WLAN and UMTS access networks. The models are light weight (can be implemented in real time monitoring), provide a measure for user perceived quality, without time consuming subjective tests. The models have potential applications in several other areas, including QoS control and optimization in network planning and content provisioning for network/service providers.(4) The applications of the proposed regression-based models were investigated in (i) optimization of content provisioning and network resource utilization and (ii) A new fuzzy sender bitrate adaptation scheme was presented at the sender side over WLAN and UMTS access networks. (5) Finally, Internet-based subjective tests that captured distortions caused by the encoder and the wireless access network for different types of contents were designed. The database of subjective results has been made available to research community as there is a lack of subjective video quality assessment databases.Partially sponsored by EU FP7 ADAMANTIUM Project (EU Contract 214751

Interventions to improve adherence to inhaled steroids for asthma.

BACKGROUND: Despite its proven efficacy in improving symptoms and reducing exacerbations, many patients with asthma are not fully adherent to their steroid inhaler. Suboptimal adherence leads to poorer clinical outcomes and increased health service utilisation, and has been identified as a contributing factor to a third of asthma deaths in the UK. Reasons for non-adherence vary, and a variety of interventions have been proposed to help people improve treatment adherence. OBJECTIVES: To assess the efficacy and safety of interventions intended to improve adherence to inhaled corticosteroids among people with asthma. SEARCH METHODS: We identified trials from the Cochrane Airways Trials Register, which contains studies identified through multiple electronic searches and handsearches of other sources. We also searched trial registries and reference lists of primary studies. We conducted the most recent searches on 18 November 2016. SELECTION CRITERIA: We included parallel and cluster randomised controlled trials of any duration conducted in any setting. We included studies reported as full-text articles, those published as abstracts only and unpublished data. We included trials of adults and children with asthma and a current prescription for an inhaled corticosteroid (ICS) (as monotherapy or in combination with a long-acting beta2-agonist (LABA)). Eligible trials compared an intervention primarily aimed at improving adherence to ICS versus usual care or an alternative intervention. DATA COLLECTION AND ANALYSIS: Two review authors screened the searches, extracted study characteristics and outcome data from included studies and assessed risk of bias. Primary outcomes were adherence to ICS, exacerbations requiring at least oral corticosteroids and asthma control. We graded results and presented evidence in 'Summary of findings' tables for each comparison.We analysed dichotomous data as odds ratios, and continuous data as mean differences or standardised mean differences, all using a random-effects model. We described skewed data narratively. We made no a priori assumptions about how trials would be categorised but conducted meta-analyses only if treatments, participants and the underlying clinical question were similar enough for pooling to make sense. MAIN RESULTS: We included 39 parallel randomised controlled trials (RCTs) involving adults and children with asthma, 28 of which (n = 16,303) contributed data to at least one meta-analysis. Follow-up ranged from two months to two years (median six months), and trials were conducted mainly in high-income countries. Most studies reported some measure of adherence to ICS and a variety of other outcomes such as quality of life and asthma control. Studies generally were at low or unclear risk of selection bias and at high risk of biases associated with blinding. We considered around half the studies to be at high risk for attrition bias and selective outcome reporting.We classified studies into four comparisons: adherence education versus control (20 studies); electronic trackers or reminders versus control (11 studies); simplified drug regimens versus usual drug regimens (four studies); and school-based directly observed therapy (three studies). Two studies are described separately.All pooled results for adherence education, electronic trackers or reminders and simplified regimens showed better adherence than controls. Analyses limited to studies using objective measures revealed that adherence education showed a benefit of 20 percentage points over control (95% confidence interval (CI) 7.52 to 32.74; five studies; low-quality evidence); electronic trackers or reminders led to better adherence of 19 percentage points (95% CI 14.47 to 25.26; six studies; moderate-quality evidence); and simplified regimens led to better adherence of 4 percentage points (95% CI 1.88 to 6.16; three studies; moderate-quality evidence). Our confidence in the evidence was reduced by risk of bias and inconsistency.Improvements in adherence were not consistently translated into observable benefit for clinical outcomes in our pooled analyses. None of the intervention types showed clear benefit for our primary clinical outcomes - exacerbations requiring an oral corticosteroid (OCS) (evidence of very low to low quality) and asthma control (evidence of low to moderate quality); nor for our secondary outcomes - unscheduled visits (evidence of very low to moderate quality) and quality of life (evidence of low to moderate quality). However, some individual studies reported observed benefits for OCS and use of healthcare services. Most school or work absence data were skewed and were difficult to interpret (evidence of low quality, when graded), and most studies did not specifically measure or report adverse events.Studies investigating the possible benefit of administering ICS at school did not measure adherence, exacerbations requiring OCS, asthma control or adverse events. One study showed fewer unscheduled visits, and another found no differences; data could not be combined. AUTHORS' CONCLUSIONS: Pooled results suggest that a variety of interventions can improve adherence. The clinical relevance of this improvement, highlighted by uncertain and inconsistent impact on clinical outcomes such as quality of life and asthma control, is less clear. We have low to moderate confidence in these findings owing to concerns about risk of bias and inconsistency. Future studies would benefit from predefining an evidence-based 'cut-off' for acceptable adherence and using objective adherence measures and validated tools and questionnaires. When possible, covert monitoring and some form of blinding or active control may help disentangle effects of the intervention from effects of inclusion in an adherence trial

Attention and Social Cognition in Virtual Reality:The effect of engagement mode and character eye-gaze

Technical developments in virtual humans are manifest in modern character design. Specifically, eye gaze offers a significant aspect of such design. There is need to consider the contribution of participant control of engagement. In the current study, we manipulated participants’ engagement with an interactive virtual reality narrative called Coffee without Words. Participants sat over coffee opposite a character in a virtual café, where they waited for their bus to be repaired. We manipulated character eye-contact with the participant. For half the participants in each condition, the character made no eye-contact for the duration of the story. For the other half, the character responded to participant eye-gaze by making and holding eye contact in return. To explore how participant engagement interacted with this manipulation, half the participants in each condition were instructed to appraise their experience as an artefact (i.e., drawing attention to technical features), while the other half were introduced to the fictional character, the narrative, and the setting as though they were real. This study allowed us to explore the contributions of character features (interactivity through eye-gaze) and cognition (attention/engagement) to the participants’ perception of realism, feelings of presence, time duration, and the extent to which they engaged with the character and represented their mental states (Theory of Mind). Importantly it does so using a highly controlled yet ecologically valid virtual experience

Content-prioritised video coding for British Sign Language communication.

Video communication of British Sign Language (BSL) is important for remote interpersonal communication and for the equal provision of services for deaf people. However, the use of video telephony and video conferencing applications for BSL communication is limited by inadequate video quality. BSL is a highly structured, linguistically complete, natural language system that expresses vocabulary and grammar visually and spatially using a complex combination of facial expressions (such as eyebrow movements, eye blinks and mouth/lip shapes), hand gestures, body movements and finger-spelling that change in space and time. Accurate natural BSL communication places specific demands on visual media applications which must compress video image data for efficient transmission. Current video compression schemes apply methods to reduce statistical redundancy and perceptual irrelevance in video image data based on a general model of Human Visual System (HVS) sensitivities. This thesis presents novel video image coding methods developed to achieve the conflicting requirements for high image quality and efficient coding. Novel methods of prioritising visually important video image content for optimised video coding are developed to exploit the HVS spatial and temporal response mechanisms of BSL users (determined by Eye Movement Tracking) and the characteristics of BSL video image content. The methods implement an accurate model of HVS foveation, applied in the spatial and temporal domains, at the pre-processing stage of a current standard-based system (H.264). Comparison of the performance of the developed and standard coding systems, using methods of video quality evaluation developed for this thesis, demonstrates improved perceived quality at low bit rates. BSL users, broadcasters and service providers benefit from the perception of high quality video over a range of available transmission bandwidths. The research community benefits from a new approach to video coding optimisation and better understanding of the communication needs of deaf people

Quality of experience in digital mobile multimedia services

People like to consume multimedia content on mobile devices. Mobile networks can deliver mobile TV services but they require large infrastructural investments and their operators need to make trade-offs to design worthwhile experiences. The approximation of how users experience networked services has shifted from the inadequate packet level Quality of Service (QoS) to the user perceived Quality of Experience (QoE) that includes content, user context and their expectations. However, QoE is lacking concrete operationalizations for the visual experience of content on small, sub-TV resolution screens displaying transcoded TV content at low bitrates. The contribution of my thesis includes both substantive and methodological results on which factors contribute to the QoE in mobile multimedia services and how. I utilised a mix of methods in both lab and field settings to assess the visual experience of multimedia content on mobile devices. This included qualitative elicitation techniques such as 14 focus groups and 75 hours of debrief interviews in six experimental studies. 343 participants watched 140 hours of realistic TV content and provided feedback through quantitative measures such as acceptability, preferences and eye-tracking. My substantive findings on the effects of size, resolution, text quality and shot types can improve multimedia models. My substantive findings show that people want to watch mobile TV at a relative size (at least 4cm of screen height) similar to living room TV setups. In order to achieve these sizes at 35cm viewing distance users require at least QCIF resolution and are willing to scale it to a much lower angular resolution (12ppd) then what video quality research has found to be the best visual quality (35ppd). My methodological findings suggest that future multimedia QoE research should use a mixed methods approach including qualitative feedback and viewing ratios akin to living room setups to meet QoE’s ambitious scope