The record producer as nexus : creative inspiration, technology and the recording industry

What is a record producer? There is a degree of mystery and uncertainty about just what goes on behind the studio door. Some producers are seen as Svengali-like figures manipulating artists into mass consumer product. Producers are sometimes seen as mere technicians whose job is simply to set up a few microphones and press the record button. Close examination of the recording process will show how far this is from a complete picture. Artists are special—they come with an inspiration, and a talent, but also with a variety of complications, and in many ways a recording studio can seem the least likely place for creative expression and for an affective performance to happen. The task of the record producer is to engage with these artists and their songs and turn these potentials into form through the technology of the recording studio. The purpose of the exercise is to disseminate this fixed form to an imagined audience—generally in the hope that this audience will prove to be real. Finding an audience is the role of the record company. A record producer must also engage with the commercial expectations of the interests that underwrite a recording. This dissertation considers three fields of interest in the recording process: the performer and the song; the technology of the recording context; and the commercial ambitions of the record company—and positions the record producer as a nexus at the interface of all three. The author reports his structured recollection of five recordings, with three different artists, that all achieved substantial commercial success. The processes are considered from the author’s perspective as the record producer, and from inception of the project to completion of the recorded work. What were the processes of engagement? Do the actions reported conform to the template of nexus? This dissertation proposes that in all recordings the function of producer/nexus is present and necessary—it exists in the interaction of the artistry and the technology. The art of record production is to engage with these artists and the songs they bring and turn these potentials into form.

Seeing music performance : visual influences on perception and experience

Drawing from ethnographic, empirical, and historical / cultural perspectives, we examine the extent to which visual aspects of music contribute to the communication that takes place between performers and their listeners. First, we introduce a framework for understanding how media and genres shape aural and visual experiences of music. Second, we present case studies of two performances, and describe the relation between visual and aural aspects of performance. Third, we report empirical evidence that visual aspects of performance reliably influence perceptions of musical structure (pitch related features) and affective interpretations of music. Finally, we trace new and old media trajectories of aural and visual dimensions of music, and highlight how our conceptions, perceptions and appreciation of music are intertwined with technological innovation and media deployment strategies.

Employee engagement : the development of a three dimensional model of engagement; and an exploration of its relationship with affective leader behaviours

This study was designed to examine affective leader behaviours, and their impact on cognitive, affective and behavioural engagement. Researchers (e.g., Cropanzano & Mitchell, 2005; Moorman et al., 1998) have called for more research to be directed toward modelling and testing sets of relationships which better approximate the complexity associated with contemporary organisational experience. This research has attempted to do this by clarifying and defining the construct of engagement, and then by examining how each of the engagement dimensions are impacted by affective leader behaviours. Specifically, a model was tested that identifies leader behaviour antecedents of cognitive, affective and behavioural engagement. Data was collected from five public-sector organisations. Structural equation modelling was used to identify the relationships between the engagement dimensions and leader behaviours. The results suggested that affective leader behaviours had a substantial direct impact on cognitive engagement, which in turn influenced affective engagement, which then influenced intent to stay and extra-role performance. The results indicated a directional process for engagement, but particularly highlighted the significant impact of affective leader behaviours as an antecedent to engagement. In general terms, the findings will provide a platform from which to develop a robust measure of engagement, and will be helpful to human resource practitioners interested in understanding the directional process of engagement and the importance of affective leadership as an antecedent to engagement.

Service staff attitudes, organisational practices and performance drivers

We provide conceptual and empirical insights elucidating how organizational practices influence service staff attitudes and behaviors and how the latter set affects organizational performance drivers. Our analyses suggest that service organizations can enhance their performance by putting in place strategies and practices that strengthen the service-oriented behaviors of their employees and reduce their intentions to leave the organization. Improved performance is accomplished through both the delivery of high quality services (enhancing organizational effectiveness) and the maintenance of frontline staff(increasing organizational efficiency). Specifically, service-oriented business strategies in the form of organizational-level service orientation and practices in the form of training directly influence the manifest service-oriented behaviors of staff. Training also indirectly affects the intention of frontline staff to leave the organization; it increases job satisfaction, which, in turn has an impact on affective commitment. Both affective and instrumental commitment were hypothesized to reduce the intentions of frontline staff to leave the organization, however only affective commitment had a significant effect.

No evidence for subliminal affective priming with emotional facial expression primes

The present study investigated whether facial expressions of emotion presented outside consciousness awareness will elicit evaluative responses as assessed in affective priming. Participants were asked to evaluate pleasant and unpleasant target words that were preceded by masked or unmasked schematic (Experiment 1) or photographic faces (Experiments 1 and 2) with happy or angry expressions. They were either required to perform the target evaluation only or to perform the target evaluation and to name the emotion expressed by the face prime. Prime-target interval was 300 ms in Experiment 1 and 80 ms in Experiment 2. Naming performance confirmed the effectiveness of the masking procedure. Affective priming was evident after unmasked primes in tasks that required naming of the facial expressions for schematic and photographic faces and after unmasked primes in tasks that did not require naming for photographic faces. No affective priming was found after masked primes. The present study failed to provide evidence for affective priming with masked face primes, however, it indicates that voluntary attention to the primes enhances affective priming.

In the pursuit of effective affective computing : the relationship between features and registration

For facial expression recognition systems to be applicable in the real world, they need to be able to detect and track a previously unseen person's face and its facial movements accurately in realistic environments. A highly plausible solution involves performing a "dense" form of alignment, where 60-70 fiducial facial points are tracked with high accuracy. The problem is that, in practice, this type of dense alignment had so far been impossible to achieve in a generic sense, mainly due to poor reliability and robustness. Instead, many expression detection methods have opted for a "coarse" form of face alignment, followed by an application of a biologically inspired appearance descriptor such as the histogram of oriented gradients or Gabor magnitudes. Encouragingly, recent advances to a number of dense alignment algorithms have demonstrated both high reliability and accuracy for unseen subjects [e.g., constrained local models (CLMs)]. This begs the question: Aside from countering against illumination variation, what do these appearance descriptors do that standard pixel representations do not? In this paper, we show that, when close to perfect alignment is obtained, there is no real benefit in employing these different appearance-based representations (under consistent illumination conditions). In fact, when misalignment does occur, we show that these appearance descriptors do work well by encoding robustness to alignment error. For this work, we compared two popular methods for dense alignment-subject-dependent active appearance models versus subject-independent CLMs-on the task of action-unit detection. These comparisons were conducted through a battery of experiments across various publicly available data sets (i.e., CK+, Pain, M3, and GEMEP-FERA). We also report our performance in the recent 2011 Facial Expression Recognition and Analysis Challenge for the subject-independent task.

Dimensions of short break destination attractiveness : a comparison of cognitive, affective and conative perceptions

Although there has been exponential growth in the number of studies of destination image appearing in the tourism literature, few have addressed the role of affective perceptions. This paper analyses the market positions held by a competitive set of destinations, through a comparison of cognitive, affective and conative perceptions. Cognitive perceptions were measured by trialling a factor analytic adaptation of importance-performance analysis. Affective perceptions were measured using an affective response grid. The alignment of the results from these techniques identified leadership positions held by two quite different destinations on two quite different dimensions of short break destination attractiveness.

Exploring emotions on #auspol : polarity, conservativism and public performance in the Twitter debate on Australian politics

The affective communication patterns of conversations on Twitter can provide insights into the culture of online communities. In this paper we apply a combined quantitative and qualitative approach to investigate the structural make-up and emotional content of tweeting activity around the hashtag #auspol (for Australian politics) in order to highlight the polarity and conservativism that characterise this highly active community of politically engaged individuals. We document the centralised structure of this particular community, which is based around a deeply committed core of contributors. Through in-depth content analysis of the tweets of participants to the online debate we explore the communicative tone, patterns of engagement and thematic drivers that shape the affective character of the community and their effect on its cohesiveness. In this way we provide a comprehensive account of the complex techno-social, linguistic and cultural factors involved in conversations that are shaped in the Twittersphere.

A pilot study on affective classification of facial images for emerging news topics

The proliferation of news reports published in online websites and news information sharing among social media users necessitates effective techniques for analysing the image, text and video data related to news topics. This paper presents the first study to classify affective facial images on emerging news topics. The proposed system dynamically monitors and selects the current hot (of great interest) news topics with strong affective interestingness using textual keywords in news articles and social media discussions. Images from the selected hot topics are extracted and classified into three categorized emotions, positive, neutral and negative, based on facial expressions of subjects in the images. Performance evaluations on two facial image datasets collected from real-world resources demonstrate the applicability and effectiveness of the proposed system in affective classification of facial images in news reports. Facial expression shows high consistency with the affective textual content in news reports for positive emotion, while only low correlation has been observed for neutral and negative. The system can be directly used for applications, such as assisting editors in choosing photos with a proper affective semantic for a certain topic during news report preparation.

The dynamics of expertise acquisition in sport : the role of affective learning design

Objectives The aim of this position paper is to discuss the role of affect in designing learning experiences to enhance expertise acquisition in sport. The design of learning environments and athlete development programmes are predicated on the successful sampling and simulation of competitive performance conditions during practice. This premise is captured by the concept of representative learning design, founded on an ecological dynamics approach to developing skill in sport, and based on the individual-environment relationship. In this paper we discuss how the effective development of expertise in sport could be enhanced by the consideration of affective constraints in the representative design of learning experiences. Conclusions Based on previous theoretical modelling and practical examples we delineate two key principles of Affective Learning Design: (i) the design of emotion-laden learning experiences that effectively simulate the constraints of performance environments in sport; (ii) recognising individualised emotional and coordination tendencies that are associated with different periods of learning. Considering the role of affect in learning environments has clear implications for how sport psychologists, athletes and coaches might collaborate to enhance the acquisition of expertise in sport.

Towards robust automatic affective classification of images using facial expressions for practical applications

Affect is an important feature of multimedia content and conveys valuable information for multimedia indexing and retrieval. Most existing studies for affective content analysis are limited to low-level features or mid-level representations, and are generally criticized for their incapacity to address the gap between low-level features and high-level human affective perception. The facial expressions of subjects in images carry important semantic information that can substantially influence human affective perception, but have been seldom investigated for affective classification of facial images towards practical applications. This paper presents an automatic image emotion detector (IED) for affective classification of practical (or non-laboratory) data using facial expressions, where a lot of “real-world” challenges are present, including pose, illumination, and size variations etc. The proposed method is novel, with its framework designed specifically to overcome these challenges using multi-view versions of face and fiducial point detectors, and a combination of point-based texture and geometry. Performance comparisons of several key parameters of relevant algorithms are conducted to explore the optimum parameters for high accuracy and fast computation speed. A comprehensive set of experiments with existing and new datasets, shows that the method is effective despite pose variations, fast, and appropriate for large-scale data, and as accurate as the method with state-of-the-art performance on laboratory-based data. The proposed method was also applied to affective classification of images from the British Broadcast Corporation (BBC) in a task typical for a practical application providing some valuable insights.