Case Study on Human-Robot Interaction of the Remote-Controlled Service Robot for Elderly and Disabled Care

The tendency of continuous aging of the population and the increasing number of people with mobility difficulties leads to increased research in the field of Assistive Service Robotics. These robots can help with daily life tasks such as reminding to take medications, serving food and drinks, controlling home appliances and even monitoring health status. When talking about assisting people in their homes, it should be noted that they will, most of the time, have to communicate with the robot themselves and be able to manage it so that they can get the most out of the robot's services. This research is focused on different methods of remote control of a mobile robot equipped with robotic manipulator. The research investigates in detail methods based on control via gestures, voice commands, and web-based graphical user interface. The capabilities of these methods for Human-Robot Interaction (HRI) have been explored in terms of usability. In this paper, we introduce a new version of the robot Robco 19, new leap motion sensor control of the robot and a new multi-channel control system. The paper presents methodology for performing the HRI experiments from human perception and summarizes the results in applications of the investigated remote control methods in real life scenarios

Methodology for Training Small Domain-specific Language Models and Its Application in Service Robot Speech Interface

The proposed paper introduces the novel methodology for training small domain-specific language models only from domain vocabulary. Proposed methodology is intended for situations, when no training data are available and preparing of appropriate deterministic grammar is not trivial task. Methodology consists of two phases. In the first phase the “random” deterministic grammar, which enables to generate all possible combination of unigrams and bigrams is constructed from vocabulary. Then, prepared random grammar serves for generating the training corpus. The “random” n-gram model is trained from generated corpus, which can be adapted in second phase. Evaluation of proposed approach has shown usability of the methodology for small domains. Results of methodology assessment favor designed method instead of constructing the appropriate deterministic grammar

Improving static audio keystroke analysis by score fusion of acoustic and timing data

In this paper we investigate the capacity of sound & timing information during typing of a password for the user identification and authentication task. The novelty of this paper lies in the comparison of performance between improved timing-based and audio-based keystroke dynamics analysis and the fusion for the keystroke authentication. We collected data of 50 people typing the same given password 100 times, divided into 4 sessions of 25 typings and tested how well the system could recognize the correct typist. Using fusion of timing (9.73%) and audio calibration scores (8.99%) described in the paper we achieved 4.65% EER (Equal Error Rate) for the authentication task. The results show the potential of using Audio Keystroke Dynamics information as a way to authenticate or identify users during log-on

Server-based Speech Technologies for Mobile Robotic Applications

Paper proposes the server-based technologies and the overall solution of the multimodal interface (speech and touchscreen) usable for mobileapplications in robotics as well as in other domain. The server-based automatic speech recognition server, able to handle several audio input streams, has been designed, developed and connected to the Android application. It receives input data stream and sends back the recognition result. The second important technology was designed and implemented to synthesize artificial speech. The server-based TTSsolution was prepared and connected. HMM-based approach was applied including recording and training of new voices. Finally, the simple client application for Android devices was developed and tested. Thediscussion of related problems is proposed also in the paper

Speech interface dialog with smart glasses

Abstract This paper describes design of elderly-user-friendly multi-mode user interface with different modules. Use of eye glasses is common among senior citizens, and it inspired us to implement interface modules on it. Indicator-based Glasses contains the Eye Blinking Detection module integrated with visual cues indicators as system feedback. The multi-mode interface provides five interaction channels by proposing audio input/output modules and Android application on smartphone device. The VoiceXML Dialog Manager implementation (VoiceON) is described and proposed for speech enabled computer initiated dialogues. Senior citizens suffering from mild and moderate dementia are the primary target group of the proposed system. The human factors of the multi-mode interface will be tested in experiment with senior citizens, and different scenarios will be evaluated