Inferring Room Semantics Using Acoustic Monitoring

Having knowledge of the environmental context of the user i.e. the knowledge of the users' indoor location and the semantics of their environment, can facilitate the development of many of location-aware applications. In this paper, we propose an acoustic monitoring technique that infers semantic knowledge about an indoor space \emph{over time,} using audio recordings from it. Our technique uses the impulse response of these spaces as well as the ambient sounds produced in them in order to determine a semantic label for them. As we process more recordings, we update our \emph{confidence} in the assigned label. We evaluate our technique on a dataset of single-speaker human speech recordings obtained in different types of rooms at three university buildings. In our evaluation, the confidence\emph{ }for the true label generally outstripped the confidence for all other labels and in some cases converged to 100\% with less than 30 samples.Comment: 2017 IEEE International Workshop on Machine Learning for Signal Processing, Sept.\ 25--28, 2017, Tokyo, Japa

Nonnative implicit phonetic training in multiple reverberant environments.

Speech intelligibility is adversely affected by reverberation, particularly when listening to a foreign language. However, little is known about how phonetic learning is affected by room acoustics. This study investigated how room reverberation impacts the acquisition of novel phonetic categories during implicit training in virtual environments. Listeners were trained to distinguish a difficult nonnative dental-retroflex contrast in phonemes presented either in a fixed room (anechoic or reverberant) or in multiple anechoic and reverberant spaces typical of everyday listening. Training employed a videogame in which phonetic stimuli were paired with rewards delivered upon successful task performance, in accordance with the task-irrelevant perceptual learning paradigm. Before and after training, participants were tested using familiar and unfamiliar speech tokens, speakers, and rooms. Implicit training performed in multiple rooms induced learning, while training in a single environment did not. The multiple-room training improvement generalized to untrained rooms and tokens, but not to untrained voices. These results show that, following implicit training, nonnative listeners can overcome the detrimental effects of reverberation and that exposure to sounds in multiple reverberant environments during training enhances implicit phonetic learning rather than disrupting it

Future bathroom: A study of user-centred design principles affecting usability, safety and satisfaction in bathrooms for people living with disabilities

Research and development work relating to assistive technology 2010-11 (Department of Health) Presented to Parliament pursuant to Section 22 of the Chronically Sick and Disabled Persons Act 197

Indoor air quality in California homes with code-required mechanical ventilation.

Data were collected in 70 detached houses built in 2011-2017 in compliance with the mechanical ventilation requirements of California's building energy efficiency standards. Each home was monitored for a 1-week period with windows closed and the central mechanical ventilation system operating. Pollutant measurements included time-resolved fine particulate matter (PM2.5 ) indoors and outdoors and formaldehyde and carbon dioxide (CO2 ) indoors. Time-integrated measurements were made for formaldehyde, NO2 , and nitrogen oxides (NOX ) indoors and outdoors. Operation of the cooktop, range hood, and other exhaust fans was continuously recorded during the monitoring period. Onetime diagnostic measurements included mechanical airflows and envelope and duct system air leakage. All homes met or were very close to meeting the ventilation requirements. On average, the dwelling unit ventilation fan moved 50% more airflow than the minimum requirement. Pollutant concentrations were similar to or lower than those reported in a 2006-2007 study of California new homes built in 2002-2005. Mean and median indoor concentrations were lower by 44% and 38% for formaldehyde and 44% and 54% for PM2.5 . Ventilation fans were operating in only 26% of homes when first visited, and the control switches in many homes did not have informative labels as required by building standards

Green Housing = Improved Health: A Winning Combination

The case studies in this paper explore the relationship between housing and health. It explains how building affordable green housing provides health benefits to low-income residentsand it identifies the benefits of green housing for the environment and energy efficiency

Narrative based Postdictive Reasoning for Cognitive Robotics

Making sense of incomplete and conflicting narrative knowledge in the presence of abnormalities, unobservable processes, and other real world considerations is a challenge and crucial requirement for cognitive robotics systems. An added challenge, even when suitably specialised action languages and reasoning systems exist, is practical integration and application within large-scale robot control frameworks. In the backdrop of an autonomous wheelchair robot control task, we report on application-driven work to realise postdiction triggered abnormality detection and re-planning for real-time robot control: (a) Narrative-based knowledge about the environment is obtained via a larger smart environment framework; and (b) abnormalities are postdicted from stable-models of an answer-set program corresponding to the robot's epistemic model. The overall reasoning is performed in the context of an approximate epistemic action theory based planner implemented via a translation to answer-set programming.Comment: Commonsense Reasoning Symposium, Ayia Napa, Cyprus, 201