A perceptual sound space for auditory displays based on sung-vowel synthesis

When designing displays for the human senses, perceptual spaces are of great importance to give intuitive access to physical attributes. Similar to how perceptual spaces based on hue, saturation, and lightness were constructed for visual color, research has explored perceptual spaces for sounds of a given timbral family based on timbre, brightness, and pitch. To promote an embodied approach to the design of auditory displays, we introduce the Vowel-Type-Pitch (VTP) space, a cylindrical sound space based on human sung vowels, whose timbres can be synthesized by the composition of acoustic formants and can be categorically labeled. Vowels are arranged along the circular dimension, while voice type and pitch of the vowel correspond to the remaining two axes of the cylindrical VTP space. The decoupling and perceptual effectiveness of the three dimensions of the VTP space are tested through a vowel labeling experiment, whose results are visualized as maps on circular slices of the VTP cylinder. We discuss implications for the design of auditory and multi-sensory displays that account for human perceptual capabilities

Embedded Knowledge-based Speech Detectors for Real-Time Recognition Tasks

Speech recognition has become common in many application domains, from dictation systems for professional practices to vocal user interfaces for people with disabilities or hands-free system control. However, so far the performance of automatic speech recognition (ASR) systems are comparable to human speech recognition (HSR) only under very strict working conditions, and in general much lower. Incorporating acoustic-phonetic knowledge into ASR design has been proven a viable approach to raise ASR accuracy. Manner of articulation attributes such as vowel, stop, fricative, approximant, nasal, and silence are examples of such knowledge. Neural networks have already been used successfully as detectors for manner of articulation attributes starting from representations of speech signal frames. In this paper, the full system implementation is described. The system has a first stage for MFCC extraction followed by a second stage implementing a sinusoidal based multi-layer perceptron for speech event classification. Implementation details over a Celoxica RC203 board are give

QRouteMe: A Multichannel Information System to Ensure Rich User-Experience in Exhibits and Museums

In this article the QRouteMe system is presented. QRouteMe is a multichannel information system built to ensure rich user experiences in exhibits and museums. The system starts from basic information about a particular exhibit or museum while delivering a wide user experience based on different distribution channels. The organization of the systems’ components allow to build different solutions that can be simultaneously delivered on different media. A wide range of media from touch-screen installations to portable devices like smartphones have been used. The used devices can communicate each others to increase the usability and the user experience for the visitors. Another important feature of the system is the definition of an inexpensive auto-localization system based on fiduciary marks distributed all around the building. In this article the system is presented from an architectural and functional point of view. A case study and analysis of experimental results are also provided in a real environment where the system was deployed

A rare case of Prinzmetal angina 3 days after coronary artery stenting with a second-generation drug-eluting stent.

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Investigating Proactive Search Support in Conversations

Conversations among people involve solving disputes, building common ground, and reinforce mutual beliefs and assumptions. Conversations often require external information that can support these human activities. In this paper, we study how a spoken conversation can be supported by a proactive search agent that listens to the conversation, detects entities mentioned in the conversation, and proactively retrieves and presents information related to the conversation. A total of 24 participants (12 pairs) were involved in informal conversations, using either the proactive search agent or a control condition that did not support conversational analysis or proactive information retrieval. Data comprising transcripts, interaction logs, questionnaires, and interviews indicated that the proactive search agent effectively augmented the conversations, affected the conversations' topical structure, and reduced the need for explicit search activity. The findings also revealed key challenges in the design of proactive search systems that assist people in natural conversations.Peer reviewe

Visual Re-Ranking for Multi-Aspect Information Retrieval

Peer reviewe

Transformation of Robotics Education in the Era of Covid-19: Challenges and Opportunities

The COVID-19 pandemic has significantly impacted many aspects of our social and professional life. To this end, Higher Education institutions reacted rather vastly to this unpreceded situation although many issues have been reported in the international literature since the emergence of the first global lockdown. As we are now transitioning back to the ‘normality’, universities and businesses consider the so-called ‘blended’ or ‘hybrid’ model as a means of facilitating the transition phase. In view of this decision, several studies can be identified wherein blended learning scenarios are proposed and described. The present work constitutes such an effort. Precisely, while adjusting the lens to the didactic of Robotics courses, we propose a blended learning model via which the laboratory activities are performed without the physical presence of the students in the physical context. The aforementioned objective is attained under the aid of the Virtual Reality technology coupled with the Digital Twin model. We hope that the ideas presented in this manuscript will motivate and inspire more researchers, instructional designers, and educators to consider the adoption of such alternative instructional techniques to mitigate the shortcomings that the remote education setting brings and further to improve the overall learning experience

A microservice architecture for predictive analytics in manufacturing

Abstract This paper discusses on the design, development and deployment of a flexible and modular platform supporting smart predictive maintenance operations, enabled by microservices architecture and virtualization technologies. Virtualization allows the platform to be deployed in a multi-tenant environment, while facilitating resource isolation and independency from specific technologies or services. Moreover, the proposed platform supports scalable data storage supporting an effective and efficient management of large volume of Industry 4.0 data. Methodologies of data-driven predictive maintenance are provided to the user as-a-service, facilitating offline training and online execution of pre-trained analytics models, while the connection of the raw data to contextual information support their understanding and interpretation, while guaranteeing interoperability across heterogeneous systems. A use case related to the predictive maintenance operations of a robotic manipulator is examined to demonstrate the effectiveness and the efficiency of the proposed platform

Designing for Mixed Reality Urban Exploration

This paper introduces a design framework for mixed reality urban exploration (MRUE), based on a concrete implementation in a historical city. The framework integrates different modalities, such as virtual reality (VR), augmented reality (AR), and haptics-audio interfaces, as well as advanced features such as personalized recommendations, social exploration, and itinerary management. It permits to address a number of concerns regarding information overload, safety, and quality of the experience, which are not sufficiently tackled in traditional non-integrated approaches. This study presents an integrated mobile platform built on top of this framework and reflects on the lessons learned.Peer reviewe