d/Deaf and Hard of Hearing (DHH) individuals often engage with music through a multimodal approach, where visual modalities are also used rather than relying on sound alone. While tools like captions and visualizers offer partial support, they often fail to capture the emotional depth and structural nuances of music. To explore new possibilities, we adopted an iterative, probe-based approach. Through a formative study with 9 DHH participants, we identified key design requirements for visualizing rhythm, emotion, and lyrics. We developed FAME (Facial Avatar for Musical Expression), a design probe that conveys music through expressive facial animation, instrument highlights, and synchronized captions, lip-syncing to lyrics or scat-singing to melodies. Through a two-phase exploratory study with 12 DHH users, we examined FAME’s efficacy, applicability, and requirements for representing musical elements. Our findings refine design requirements for avatar-based systems and highlight the potential of avatars as expressive and socially meaningful tools for music accessibility.

Sound effects (SFX) are critical to video storytelling by immersing viewers, directing attention, and shaping emotion. However, crafting an effective soundscape is difficult: creators must decide how to source, place, layer, and mix sounds to support the narrative. Generative text-to-SFX tools enable users to create custom sounds, but creators often struggle to describe sounds with words and lack control over individual stems in premixed outputs. We propose SoundStager, an AI-assisted tool for designing generative soundscapes for video. SoundStager analyzes the video narrative to create layered audio scenes (of keynote, signal, soundmark, and archetypal sounds) and supports iterative refinement through a combination of conversational and analog controls. SoundStager’s design was informed by formative studies with six professional sound designers, six video creators, and insights from sound design literature. Our user evaluation with twelve video creators shows that SoundStager enables users to quickly create satisfactory soundscapes while retaining creative control.

Music can play an important role in the lives of some Deaf and Hardof-Hearing (DHH) individuals, facilitating emotional expression, storytelling, and social interaction despite differences in hearing ability and identity.While prior human-computer interaction (HCI) research has introduced various functional advancements to enhance their music experiences, a deeper exploration of broader user experiences and inclusive design strategies remains necessary.To address the real-life challenges DHH individuals face in everyday music activities, we conducted focus group interviews in South Korea with 39 DHH individuals and 9 music experts.Our analysis identified six dimensions of everyday music activities organized by engagement type and social level, highlighting the distinct challenges and preferences DHH individuals encounter in musical contexts.Based on these insights, we propose design implications for fostering more inclusive music experiences, extending beyond individual engagement to include community and mixed-group interactions.This work provides a comprehensive framework to inform future HCI research and guide the development of inclusive technologies that better support DHH individuals' diverse musical experiences.

Affective and prosodic captions convey not only what a speaker says, but also how they say it-louder words may appear thicker, quieter ones thinner; angry in red, calm in blue.These captions can improve access, satisfaction, and engagement for d/Deaf and Hard-of-Hearing (dhh) users.While prior work has explored their design space, it has focused largely on dhh participants in North America, limiting generalizability beyond English and Latin-based scripts.To uncover the role of culture and language, we ran an exploratory study with 49 dhh participants from North America and South Korea using CuCap, a tool that allowed them to personalize which speech features were displayed, and how.While emotion visualization was a universally favored choice, confirming prior findings, prosody preferences varied across cultures, reflecting linguistic and hearing factors.These findings point to the need for flexible captioning systems that account for cultural, linguistic, and individual differences.

Although engagement in self-directed wellness exercises typically declines over time, integrating social support such as coaching can sustain it. However, traditional forms of support are often inaccessible due to the high costs and complex coordination. Large Language Models (LLMs) show promise in providing human-like dialogues that could emulate social support. Yet, in-depth, in situ investigations of LLMs to support behavior change remain underexplored. We conducted two randomized experiments to assess the impact of LLM agents on user engagement with mindfulness exercises. First, a single-session study, involved 502 crowdworkers; second, a three-week study, included 54 participants. We explored two types of LLM agents: one providing information and another facilitating self-reflection. Both agents enhanced users' intentions to practice mindfulness. However, only the information-providing LLM agent, featuring a friendly persona, significantly improved engagement with the exercises. Our findings suggest that specific LLM agents may bridge the social support gap in digital health interventions.

Creating dedicated accounts to post users’ pet content is a growing trend on Instagram. While these account owners derive joy from this pursuit, they may also struggle with criticisms and challenges. Yet, there remains a knowledge gap on how pet account owners manage their pets’ online presence and navigate these obstacles successfully. Drawing from interviews with 21 Instagram pet account owners, we uncover the motivations behind pet account creation, spanning personal, altruistic, and commercial goals. We learn about the strategies employed for crafting their pets’ online identities and personas, as well as the challenges faced by both owners and their pets in navigating the complexities of digital identity management. We discuss the evolving dynamics between humans and their pets, positioning pet identity cultivation as a form of collaborative work, akin to the “third shift”, highlighting the need to design interfaces that support this unique identity management process.

Song signing is a method practiced by people who are d/Deaf and non-d/Deaf individuals to visually represent music and make music accessible through sign language and body movements. Although there is growing interest in song signing, there is a lack of understanding on what d/Deaf people value about song signing and how to make song signing productions that they would consider acceptable. We conducted semi-structured interviews with 12 d/Deaf participants to gain a deeper understanding of what they value in music and song signing. We then interviewed 14 song signers to understand their experiences and processes in creating song signing performances. From this study, we identify three complex, interrelated layers of the song signing creation process and discuss how they can be supported and completed to potentially bridge the cultural divide between the d/Deaf and non-d/Deaf audiences and guide more culturally responsive creation of music.

With the recent advances in Internet of Things and cyber-physical systems technologies, smart industrial systems support configurable processes consisting of human interactions as well as hard real-time functions. This implies that irregularly arriving interactive tasks and traditional hard real-time tasks coexist. As the characteristics of the tasks are heterogeneous, it is not an easy matter to schedule them all at once. To cope with this situation, this article presents a new task scheduling policy that uses the notion of “virtual real-time task” and two-phase scheduling. As hard real-time tasks must keep their deadlines, we perform offline scheduling based on genetic algorithms beforehand. This determines the processor's voltage level and memory location of each task and also reserves the virtual real-time tasks for interactive tasks. When interactive tasks arrive during the execution, online scheduling is performed on the time slot of the virtual real-time tasks. As interactive workloads evolve over time, we monitor them and periodically update the offline scheduling. Experimental results show that the proposed policy reduces the energy consumption by 66.8% on average without deadline misses and also supports the waiting time of less than 3 (s) for interactive tasks.

A new task scheduling algorithm that schedules mixed task set consisting of real-time and interactive tasks is presented. Our algorithm aims at minimizing the power consumption of the system with the reasonable response time of interactive tasks as well as the deadline guarantees of real-time tasks. Experimental results show that the proposed algorithm improves the power consumption by 23% on average.