Application of Wearable Computer and ASR Technology in an Underground Mine to Support Mine Supervision of the Heavy Machinery Chamber.

Systems that use automatic speech recognition in industry are becoming more and more popular. They bring benefits especially in cases when the user's hands are often busy or the environment does not allow the use of a keyboard. However, the accuracy of algorithms is still a big challenge. The article describes the attempt to use ASR in the underground mining industry as an improvement in the records of work in the heavy machinery chamber by a foreman. Particular attention was paid to the factors that in this case will have a negative impact on speech recognition: the influence of the environment, specialized mining vocabulary, and the learning curve. First, the foreman's workflow and documentation were recognized. This allowed for the selection of functionalities that should be included in the application. A dictionary of specialized mining vocabulary and a source database were developed which, in combination with the string matching algorithms, aim to improve correct speech recognition. Text mining analysis, machine learning methods were used to create functionalities that provide assistance in registering information. Finally, the prototype of the application was tested in the mining environment and the accuracy of the results were presented.

Multi-modal assessment of on-road demand of voice and manual phone calling and voice navigation entry across two embedded vehicle systems.

One purpose of integrating voice interfaces into embedded vehicle systems is to reduce drivers' visual and manual distractions with 'infotainment' technologies. However, there is scant research on actual benefits in production vehicles or how different interface designs affect attentional demands. Driving performance, visual engagement, and indices of workload (heart rate, skin conductance, subjective ratings) were assessed in 80 drivers randomly assigned to drive a 2013 Chevrolet Equinox or Volvo XC60. The Chevrolet MyLink system allowed completing tasks with one voice command, while the Volvo Sensus required multiple commands to navigate the menu structure. When calling a phone contact, both voice systems reduced visual demand relative to the visual-manual interfaces, with reductions for drivers in the Equinox being greater. The Equinox 'one-shot' voice command showed advantages during contact calling but had significantly higher error rates than Sensus during destination address entry. For both secondary tasks, neither voice interface entirely eliminated visual demand. Practitioner Summary: The findings reinforce the observation that most, if not all, automotive auditory-vocal interfaces are multi-modal interfaces in which the full range of potential demands (auditory, vocal, visual, manipulative, cognitive, tactile, etc.) need to be considered in developing optimal implementations and evaluating drivers' interaction with the systems. Social Media: In-vehicle voice-interfaces can reduce visual demand but do not eliminate it and all types of demand need to be taken into account in a comprehensive evaluation.

Multi-modal demands of a smartphone used to place calls and enter addresses during highway driving relative to two embedded systems.

There is limited research on trade-offs in demand between manual and voice interfaces of embedded and portable technologies. Mehler et al. identified differences in driving performance, visual engagement and workload between two contrasting embedded vehicle system designs (Chevrolet MyLink and Volvo Sensus). The current study extends this work by comparing these embedded systems with a smartphone (Samsung Galaxy S4). None of the voice interfaces eliminated visual demand. Relative to placing calls manually, both embedded voice interfaces resulted in less eyes-off-road time than the smartphone. Errors were most frequent when calling contacts using the smartphone. The smartphone and MyLink allowed addresses to be entered using compound voice commands resulting in shorter eyes-off-road time compared with the menu-based Sensus but with many more errors. Driving performance and physiological measures indicated increased demand when performing secondary tasks relative to 'just driving', but were not significantly different between the smartphone and embedded systems. Practitioner Summary: The findings show that embedded system and portable device voice interfaces place fewer visual demands on the driver than manual interfaces, but they also underscore how differences in system designs can significantly affect not only the demands placed on drivers, but also the successful completion of tasks.

The impact of environmental noise on drivers' cognitive abilities: A case study on in-vehicle voice interaction interfaces.

To investigate the impact of environmental noise on the cognitive abilities of drivers, this study, using in-vehicle voice interaction as an example, conducted laboratory experiments to assess the effects of road traffic noise, entertainment noise, and white noise stimuli on drivers' attention and short-term memory. The noise levels simulated to mimic acoustic conditions during car driving ranged from 35 dB(A) to 65 dB(A). The conclusions drawn were as follows: (1) Noise levels directly influenced subjective annoyance levels, with annoyance linearly increasing as noise levels escalated; (2) Both attention and short-term memory task reaction times of drivers were significantly influenced by noise types. Compared to traffic noise and white noise, drivers' cognitive efficiency was lower under entertainment noise. (3) Performance in complex cognitive tasks was more susceptible to noise levels compared to simple cognitive tasks; (4) Experimentally, it was found that drivers exhibited the highest cognitive efficiency in cognitive tasks when the environmental noise level was 55 dB(A), as opposed to noise levels of 35 dB(A), 45 dB(A), and 65 dB(A).

Effectiveness and User Perception of an In-Vehicle Voice Warning for Hypoglycemia: Development and Feasibility Trial.

BACKGROUND: Hypoglycemia is a frequent and acute complication in type 1 diabetes mellitus (T1DM) and is associated with a higher risk of car mishaps. Currently, hypoglycemia can be detected and signaled through flash glucose monitoring or continuous glucose monitoring devices, which require manual and visual interaction, thereby removing the focus of attention from the driving task. Hypoglycemia causes a decrease in attention, thereby challenging the safety of using such devices behind the wheel. Here, we present an investigation of a hands-free technology-a voice warning that can potentially be delivered via an in-vehicle voice assistant. OBJECTIVE: This study aims to investigate the feasibility of an in-vehicle voice warning for hypoglycemia, evaluating both its effectiveness and user perception. METHODS: We designed a voice warning and evaluated it in 3 studies. In all studies, participants received a voice warning while driving. Study 0 (n=10) assessed the feasibility of using a voice warning with healthy participants driving in a simulator. Study 1 (n=18) assessed the voice warning in participants with T1DM. Study 2 (n=20) assessed the voice warning in participants with T1DM undergoing hypoglycemia while driving in a real car. We measured participants' self-reported perception of the voice warning (with a user experience scale in study 0 and with acceptance, alliance, and trust scales in studies 1 and 2) and compliance behavior (whether they stopped the car and reaction time). In addition, we assessed technology affinity and collected the participants' verbal feedback. RESULTS: Technology affinity was similar across studies and approximately 70% of the maximal value. Perception measure of the voice warning was approximately 62% to 78% in the simulated driving and 34% to 56% in real-world driving. Perception correlated with technology affinity on specific constructs (eg, Affinity for Technology Interaction score and intention to use, optimism and performance expectancy, behavioral intention, Session Alliance Inventory score, innovativeness and hedonic motivation, and negative correlations between discomfort and behavioral intention and discomfort and competence trust; all P<.05). Compliance was 100% in all studies, whereas reaction time was higher in study 1 (mean 23, SD 5.2 seconds) than in study 0 (mean 12.6, SD 5.7 seconds) and study 2 (mean 14.6, SD 4.3 seconds). Finally, verbal feedback showed that the participants preferred the voice warning to be less verbose and interactive. CONCLUSIONS: This is the first study to investigate the feasibility of an in-vehicle voice warning for hypoglycemia. Drivers find such an implementation useful and effective in a simulated environment, but improvements are needed in the real-world driving context. This study is a kickoff for the use of in-vehicle voice assistants for digital health interventions.

Designing voice interfaces to support mindfulness-based pain management.

Objective: Chronic pain is a critical public health issue affecting approximately 20% of the adult population in the United States. Given the opioid crisis, there has been an urgent focus on non-addictive pain management methods including mindfulness-based stress reduction (MBSR). Prior work has successfully used MBSR for pain management. However, ensuring longitudinal engagement in MBSR practices remains a serious challenge. In this work, we explore the utility of a voice interface to support MBSR home practice. Methods: We interviewed 10 mindfulness program facilitators to understand how such a technology might fit in the context of the MBSR class and identify potential usability issues with our prototype. We then used directed content analysis to identify key themes and sub-themes within the interview data. Results: Our findings show that facilitators supported the use of the voice interface for MBSR, particularly for individuals with limited motor function. Facilitators also highlighted the unique affordances of voice interfaces, including perceived social presence, to support sustained engagement. Conclusion: We demonstrate the acceptability of a voice interface to support home practice for MBSR participants among trained mindfulness facilitators. Based on our findings, we outline design recommendations for technologies aiming to provide longitudinal support for mindfulness-based interventions. Future work should further these efforts toward making non-addictive pain management interventions accessible and efficacious for a wide audience of users.

Factors affecting drivers' off-road glance behavior while interacting with in-vehicle voice interfaces.

In-vehicle voice-based interfaces have been massively embedded in modern vehicles as a countermeasure to visual-manual distractions. However, limited data are available regarding the actual visual demands imposed on the driver when interacting with such an interface. How those factors that are associated with the drivers themselves affect their visual behavior when interacting with an in-vehicle voice-based interface remains understudied. This study focused on investigating factors affecting drivers' off-road visual behavior while interacting with a voice-based interface. A secondary data analysis leveraging structural equation modeling was performed based on data collected from a large-scale field experiment wherein participants drove a vehicle on the highway and performed a series of tasks using an in-vehicle voice interface. The results indicate that while voice-based interfaces are designed to help reduce drivers' visual demands, drivers can still direct their eyes off the road for a prolonged period of time during the interaction and exhibit potentially risky visual behavior. In addition, individual-level factors can exert influence on drivers' off-road visual behavior in such a way that older drivers and drivers with higher trust in technologies are associated with more long eyes-off-road glances when interacting with a voice-based interface. To promote the general public's adoption of in-vehicle voice interfaces and support safe interactions, we recommend relevant research and system design consider drivers' trust in, perceptions, and previous usage of similar technologies, as well as their individual characteristics such as age.

An indoor navigation system for the visually impaired.

Navigation in indoor environments is highly challenging for the severely visually impaired, particularly in spaces visited for the first time. Several solutions have been proposed to deal with this challenge. Although some of them have shown to be useful in real scenarios, they involve an important deployment effort or use artifacts that are not natural for blind users. This paper presents an indoor navigation system that was designed taking into consideration usability as the quality requirement to be maximized. This solution enables one to identify the position of a person and calculates the velocity and direction of his movements. Using this information, the system determines the user's trajectory, locates possible obstacles in that route, and offers navigation information to the user. The solution has been evaluated using two experimental scenarios. Although the results are still not enough to provide strong conclusions, they indicate that the system is suitable to guide visually impaired people through an unknown built environment.

Voice Interface Technology Adoption by Patients With Heart Failure: Pilot Comparison Study.

BACKGROUND: Heart failure (HF) is associated with high mortality rates and high costs, and self-care is crucial in the management of the condition. Telehealth can promote patients' self-care while providing frequent feedback to their health care providers about the patient's compliance and symptoms. A number of technologies have been considered in the literature to facilitate telehealth in patients with HF. An important factor in the adoption of these technologies is their ease of use. Conversational agent technologies using a voice interface can be a good option because they use speech recognition to communicate with patients. OBJECTIVE: The aim of this paper is to study the engagement of patients with HF with voice interface technology. In particular, we investigate which patient characteristics are linked to increased technology use. METHODS: We used data from two separate HF patient groups that used different telehealth technologies over a 90-day period. Each group used a different type of voice interface; however, the scripts followed by the two technologies were identical. One technology was based on Amazon's Alexa (Alexa+), and in the other technology, patients used a tablet to interact with a visually animated and voice-enabled avatar (Avatar). Patient engagement was measured as the number of days on which the patients used the technology during the study period. We used multiple linear regression to model engagement with the technology based on patients' demographic and clinical characteristics and past technology use. RESULTS: In both populations, the patients were predominantly male and Black, had an average age of 55 years, and had HF for an average of 7 years. The only patient characteristic that was statistically different (P=.008) between the two populations was the number of medications they took to manage HF, with a mean of 8.7 (SD 4.0) for Alexa+ and 5.8 (SD 3.4) for Avatar patients. The regression model on the combined population shows that older patients used the technology more frequently (an additional 1.19 days of use for each additional year of age; P=.004). The number of medications to manage HF was negatively associated with use (-5.49; P=.005), and Black patients used the technology less frequently than other patients with similar characteristics (-15.96; P=.08). CONCLUSIONS: Older patients' higher engagement with telehealth is consistent with findings from previous studies, confirming the acceptability of technology in this subset of patients with HF. However, we also found that a higher number of HF medications, which may be correlated with a higher disease burden, is negatively associated with telehealth use. Finally, the lower engagement of Black patients highlights the need for further study to identify the reasons behind this lower engagement, including the possible role of social determinants of health, and potentially create technologies that are better tailored for this population.