In Intensive Care Units (ICUs), excessive non-human and human sounds cause behavioural and psychological problems in patients and reduce professionals' job satisfaction and performance. Rather than relying solely on quantitative (psycho/acoustic) metrics, their combination with qualitative data (soundscape descriptors) provides the most reliable method to assess this context, as it considers the perceived environment. Moreover, sound event detection (SED) and classification techniques enhance the reliability of the assessment model. However, they also raise ethical concerns regarding vulnerable patients' rights. Therefore, the development of audio data ethics is essential for designing research strategies that strike a balance between patients' rights and research effectiveness. This study aims to define audio data ethics based on expert interviews and outline the basics of a tool to identify and assess risks for mitigation strategies. Results indicate that quantitative and qualitative data present minimal ethical risks, but audio recording for event identification poses significant ones. Managing these risks helps prevent patient re-identification, discrimination, and mistrust in research. The results will be validated in an ICU.

In an earlier study, we explored the intersection between human perception of sound, Machine Listening, and their potential societal and environmental impact with experts in computer science, art and philosophy, design, and ethics. As a follow-up work, we explored SoundAI applications through two MSc design student projects at TU Delft on the topics of building cultural bonds by generating new community soundscapes and increasing awareness on biodiversity by focussing on other-than-human noise sensitivity. This paper presents these two use cases with societal, environmental, and ethical considerations, and suitable AI techniques. The proposed applications manifest themselves as promoting accessibility, environmental awareness, and community well-being while mitigating ethical risks in privacy and ownership. These two design explorations allow us to imagine early AI applications for sound with their opportunities and limitations. It is our intention that SoundAI responds to the real needs of individuals, natural habitats, and other species to make a positive societal and environmental impact.

The hospital soundscape is known for high noise levels and a perception of chaos, leading to concerns about its impact on patients, families, professionals, and other hospital staff. This study investigates the relationship between sound, Annoyance, and sleep quality in a multi-patient neurology ward. A mixed-methods approach was employed. Interviews were conducted with medical staff (n = 7) to understand their experiences with sound. Questionnaires and sleep tracking devices (n = 20) assessed patient sleep quality and Annoyance caused by sound events. In addition, listeners (n = 28) annotated 429 nighttime audio recordings to identify sound sources and rate Annoyance level, which we considered the key emotional descriptor for patients. Over 9,200 sound events were analysed. While snoring, a patient-generated sound dominated the nighttime soundscape and was highly rated for Annoyance, and staff-generated sounds such as speech and footsteps were found to contribute more to accumulated Annoyance due to their extended duration. This study suggests that patient sleep quality can be improved by focusing on design interventions that reduce the impact of specific sounds. These might include raising awareness among staff about activities that might produce annoying sounds and implementing strategies to mitigate their disruptive effects.

There is an increased awareness of how the quality of the acoustic environment impacts the lives of human beings. Several studies have shown that sound pollution has adverse effects on many populations, from infants to adults, in different environments and workplaces. Hospitals are susceptible environments that require special attention since sound can aggravate patients' health issues and negatively impact the performance of healthcare professionals. This paper focuses on Neonatal Intensive Care Units (NICU) as an especially sensitive case representing a hostile acoustic environment in which healthcare professionals have little awareness of how unwanted sounds impact the perceived quality of the soundscape. We performed a semi-systematic review of scientific literature on sound assessment studies in NICU from 2001. A thematic analysis was performed to identify emerging themes that informed the analysis of 27 technological solutions for the assessment of sound quality in indoor and outdoor environments. Solutions were categorized by functions and evaluation methods and grouped according to the characteristics of the design components, i.e., acquisition, computation, and communication strategies. Results highlight a lack of solutions to assess the qualitative characteristics of indoor environments such as NICU and forecast the footprint that different sound sources have on the indoor soundscape. Such solutions are urgently needed to empower healthcare professionals, and especially nurses, to actively modify and prevent the negative impact of unwanted sounds on NICU and critical care soundscape.

Introduction: It has proven a hard challenge to stimulate climate action with climate data. While scientists communicate through words, numbers, and diagrams, artists use movement, images, and sound. Sonification, the translation of data into sound, and visualization, offer techniques for representing climate data with often innovative and exciting results. The concept of sonification was initially defined in terms of engineering, and while this view remains dominant, researchers increasingly make use of knowledge from electroacoustic music (EAM) to make sonifications more convincing. Methods: The Aesthetic Perspective Space (APS) is a two-dimensional model that bridges utilitarian-oriented sonification and music. We started with a review of 395 sonification projects, from which a corpus of 32 that target climate change was chosen; a subset of 18 also integrate visualization of the data. To clarify relationships with climate data sources, we determined topics and subtopics in a hierarchical classification. Media duration and lexical diversity in descriptions were determined. We developed a protocol to span the APS dimensions, Intentionality and Indexicality, and evaluated its circumplexity. Results: We constructed 25 scales to cover a range of qualitative characteristics applicable to sonification and sonification-visualization projects, and through exploratory factor analysis, identified five essential aspects of the project descriptions, labeled Action, Technical, Context, Perspective, and Visualization. Through linear regression modeling, we investigated the prediction of aesthetic perspective from essential aspects, media duration, and lexical diversity. Significant regressions across the corpus were identified for Perspective (ß = 0.41^***) and lexical diversity (ß = −0.23^*) on Intentionality, and for Perspective (ß = 0.36^***) and Duration (logarithmic; ß = −0.25^*) on Indexicality. Discussion: We discuss how these relationships play out in specific projects, also within the corpus subset that integrated data visualization, as well as broader implications of aesthetics on design techniques for multimodal representations aimed at conveying scientific data. Our approach is informed by the ongoing discussion in sound design and auditory perception research communities on the relationship between sonification and EAM. Through its analysis of topics, qualitative characteristics, and aesthetics across a range of projects, our study contributes to the development of empirically founded design techniques, applicable to climate science communication and other fields.

El trabajo por superposición de tramas de información gráfica ha sido una metodología de desarrollo proyectual utilizada por grandes arquitectos como alternativa a otros procesos metodológicos de diseño. Estas capas pueden estar referidas a aspectos tangibles de la arquitectura y el diseño urbano, esto es, elementos físicos, tocables, o a esas tensiones invisibles, intangibles que aportan valor sustancial a la arquitectura. La experimentación con este tipo de trabajo aporta al alumnado una metodología complementaria a otros procesos más lineales y controlados, permitiendo que la propia superposición de capas sugiera la aparición de ‘estructuras de sucesos’ inesperadas. En este artículo se presenta la secuencia de experimentación realizada sobre estas bases metodológicas en tres ejercicios consecutivos desde la composición en dos dimensiones, pasando por lo matérico hasta la creación de un proyecto completo. La pandemia COVID-19 entra a formar parte de estos estratos superpuestos de capas influyendo sustancialmente sobre el resultado final. Overlapping graphic information patterns is an architectural design methodology used in the recent past by renowned architects as an alternative way to other design processes. Design layers can be referred to tangible aspects of architecture and design, this is, physically touchable elements, or to those invisible tensions that add core substantial value to architecture. By experimenting with this kind of work, students acquire a complementary methodology to other more linear and controlled processes, allowing them to bump into unexpected ‘structures of events’ suggested by the very overlapping layers. In this article we present the experimental sequence developed on this methodological basis over three consecutive exercises, from a two-dimensional composition, going through materiality until the pursuit of a whole architectural project. The COVID-19 pandemic enters the picture to take part of this stratified array of layers and substantially influence the final result.

Water distribution systems are undergoing a process of intensive digitalization, adopting networked devices for monitoring and control. While this transition improves efficiency and reliability, these infrastructures are increasingly exposed to cyber-attacks. Cyber-attacks engender anomalous system behaviors which can be detected by data-driven algorithms monitoring sensors readings to disclose the presence of potential threats. At the same time, the use of sonification in real time process monitoring has grown in importance as a valid alternative to avoid information overload and allowing peripheral monitoring. Our project aims to design a sonification system allowing human operators to take better decisions on anomalous behavior while occupied in other (mainly visual) tasks. Using a state-of-the-art detection algorithm and data sets from the Battle of the Attack Detection Algorithms, a series of sonification prototypes were designed and tested in the real world. This paper illustrates the design process and the experimental data collected, as well results and plans for future steps.