Alan F. Blackwell

Joseph Cameron, Alan Blackwell

Understanding and manipulating timbre is central to audio synthesis, yet this remains under-explored in machine learning due to a lack of annotated datasets linking perceptual timbre dimensions to semantic descriptors. We present the Semantic Timbre Dataset, a curated collection of monophonic electric guitar sounds, each labeled with one of 19 semantic timbre descriptors and corresponding magnitudes. These descriptors were derived from a qualitative analysis of physical and virtual guitar effect units and applied systematically to clean guitar tones. The dataset bridges perceptual timbre and machine learning representations, supporting learning for timbre control and semantic audio generation. We validate the dataset by training a variational autoencoder (VAE) on its latent space and evaluating it using human perceptual judgments and descriptor classifiers. Results show that the VAE captures timbral structure and enables smooth interpolation across descriptors. We release the dataset, code, and evaluation protocols to support timbre-aware generative AI research.

Joseph Cameron, Alan Blackwell

We present a comparative evaluation of latent space organization in three Variational Autoencoders (VAEs) for musical timbre generation: an unsupervised VAE, a descriptor-conditioned VAE, and a VAE conditioned on continuous perceptual features from the AudioCommons timbral models. Using a curated dataset of electric guitar sounds labeled with 19 semantic descriptors across four intensity levels, we assess each model's latent structure with a suite of clustering and interpretability metrics. These include silhouette scores, timbre descriptor compactness, pitch-conditional separation, trajectory linearity, and cross-pitch consistency. Our findings show that conditioning on perceptual features yields a more compact, discriminative, and pitch-invariant latent space, outperforming both the unsupervised and discrete descriptor-conditioned models. This work highlights the limitations of one-hot semantic conditioning and provides methodological tools for evaluating timbre latent spaces, contributing to the development of more controllable and interpretable generative audio models.

Alessandro Trevisan, Harry Giddens, Sarah Dillon et al.

What can we learn about language from studying how it is used by ChatGPT and other large language model (LLM)-based chatbots? In this paper, we analyse the distinctive character of language generated by ChatGPT, in relation to questions raised by natural language processing pioneer, and student of Wittgenstein, Margaret Masterman. Following frequent complaints that LLM-based chatbots produce "slop," or even "bullshit," in the sense of Frankfurt's popular monograph On Bullshit, we conduct an empirical study to contrast the language of 1,000 scientific publications with typical text generated by ChatGPT. We then explore whether the same language features can be detected in two well-known contexts of social dysfunction: George Orwell's critique of political speech, and David Graeber's characterisation of bullshit jobs. Using simple hypothesis-testing methods, we demonstrate that a statistical model of sloppy bullshit can reliably relate the Frankfurtian artificial bullshit of ChatGPT to the political and workplace functions of bullshit as observed in natural human language.

Mao Mao, Alan F. Blackwell, David A. Good

This paper describes a qualitative study of retirees' social and personal practices via digital music technologies in the context of community music. We conducted a diary study, and interviewed retired community musicians who are experiencing transition to retirement. Amongst challenges due to ageing and retirement, retirees participating in community music often experience discontinuity of identity caused by the lack of social and personal support after retirement, and also report lack of interest in using new technologies. Life transition theory was used to understand retirees' perception and strategies of identity navigation, informing the design of community-oriented online music services. We deepened our understanding of retirement transitions with technologies by showing how retirees participating in community music make sense of new rules and norms after retirement. A key finding is that retirees reconstruct identities by connecting with music communities, through which they can develop an understanding of unfamiliar patterns of the retired life, and gain support musically and socially. Technologies act as 'boundary objects' for communication between digital and physical artefacts, personal and social relationships. We highlight the importance of managing artefactual and interpersonal boundaries when designing online services for individual and communities in transitions.

Charith Perera, Saeed Aghaee, Ramsey Faragher et al.

Location sensing is a key enabling technology for Ubicomp to support contextual interaction. However, the laboratories where calibrated testing of location technologies is done are very different to the domestic situations where `context' is a problematic social construct. This study reports measurements of Bluetooth beacons, informed by laboratory studies, but done in diverse domestic settings. The design of these surveys has been motivated by the natural environment implied in the Bluetooth beacon standards - relating the technical environment of the beacon to the function of spaces within the home. This research method can be considered as a situated, `ethnographic' technical response to the study of physical infrastructure that arises through social processes. The results offer insights for the future design of `seamful' approaches to indoor location sensing, and to the ways that context might be constructed and interpreted in a seamful manner.

Tommy Nilsson, Alan Blackwell, Carl Hogsden et al.

BLE (Bluetooth Low Energy) is a new wireless communication technology that, thanks to reduced power consumption, promises to facilitate communication between computing devices and help us harness their power in environments and contexts previously untouched by information technology. Museums and other facilities housing various cultural content are a particularly interesting area of application. The University of Cambridge Museums consortium has put considerable effort into researching the potential uses of emerging technologies such as BLE to unlock new experiences enriching the way we engage with cultural information. As a part of this research initiative, our ambition has been to examine the challenges and opportunities introduced by the introduction of a BLE-centred system into the museum context. We present an assessment of the potential offered by this technology and of the design approaches that might yield the best results when developing BLE-centred experiences for museum environments. A pivotal part of our project consisted of designing, developing and evaluating a prototype mobile location-based BLE-centred game. A number of technical problems, such as unstable and fluctuating signal strength, were encountered throughout the project lifecycle. Instead of attempting to eliminate such problems, we argued in favour of embracing them and turning them into a cornerstone of the gameplay. Our study suggested that this alternative seamful design approach yields particularly good results when deploying the technology in public environments. The project outcome also demonstrated the potential of BLE-centred solutions to reach out and engage new demographics, especially children, extending their interest in museum visits.

Tommy Nilsson, Carl Hogsden, Charith Perera et al.

The application of mobile computing is currently altering patterns of our behavior to a greater degree than perhaps any other invention. In combination with the introduction of power efficient wireless communication technologies, such as Bluetooth Low Energy (BLE), designers are today increasingly empowered to shape the way we interact with our physical surroundings and thus build entirely new experiences. However, our evaluations of BLE and its abilities to facilitate mobile location-based experiences in public environments revealed a number of potential problems. Most notably, the position and orientation of the user in combination with various environmental factors, such as crowds of people traversing the space, were found to cause major fluctuations of the received BLE signal strength. These issues are rendering a seamless functioning of any location-based application practically impossible. Instead of achieving seamlessness by eliminating these technical issues, we thus choose to advocate the use of a seamful approach, i.e. to reveal and exploit these problems and turn them into a part of the actual experience. In order to demonstrate the viability of this approach, we designed, implemented and evaluated the Ghost Detector - an educational location-based museum game for children. By presenting a qualitative evaluation of this game and by motivating our design decisions, this paper provides insight into some of the challenges and possible solutions connected to the process of developing location-based BLE-enabled experiences for public cultural spaces.

Charith Perera, Saeed Aghaee, Alan Blackwell

This study explores the use of natural language to give instructions that might be interpreted by Internet of Things (IoT) devices in a domestic `smart home' environment. We start from the proposition that reminders can be considered as a type of end-user programming, in which the executed actions might be performed either by an automated agent or by the author of the reminder. We conducted an experiment in which people wrote sticky notes specifying future actions in their home. In different conditions, these notes were addressed to themselves, to others, or to a computer agent.We analyse the linguistic features and strategies that are used to achieve these tasks, including the use of graphical resources as an informal visual language. The findings provide a basis for design guidance related to end-user development for the Internet of Things.