12 research outputs found

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

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    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

    Car Trajectory Correction and Presentation Using Google Maps

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    This paper describes a trajectory correction algorithm which calculates the kinetic parameters of the tracked object (car using GPS data from tracking device) and detects faulty GPS samples. Input parameters contain GPS geographical coordinates of the object and the timestamp code of capturing the position. Based on these data and physical object limits, which the operator could modify, the algorithm decides if the sample is precise or faulty. In the case of faulty sample the algorithm suggests the estimated location of the point using Kalman filter implementation and the results are presented on the map using online web interface. When the operator confirms a predicted sample, the previous predicted (not confirmed samples) are recomputed using a backward correction algorithm. The final corrected trajectory is presented using a developed specialized interactive web interface with embedded Google maps API

    Building of Broadcast News Database for Evaluation of the Automated Subtitling Service

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    This paper describes the process of recording, annotation, correction and evaluation of the new Broadcast News (BN) speech database named KEMT-BN2, as an extension for our older KEMT-BN1 and COST-278 databases used for automatic Slovak continuous speech recognition development. The database utilisation and statistics are presented. This database was prepared for evaluation of the automated BN transcription system, developed in our laboratory, which is mainly used for subtitle generation for recorded BN shows. The speech database is the key part of the acoustic models training for specific domains and also for speaker and anchor adapted models creation

    Acoustical user identification based on MFCC analysis of keystrokes

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    This paper introduces a novel approach of person identification using acoustical monitoring of typing the required word on the monitored keyboard. This experiment was motivated by the idea of COST IC1106 (Integrating Biometrics and Forensics for the Digital Age) partners to acoustically analyse the captured keystroke dynamics database using widely used time-invariant mathematical models tools. The MFCC (Mel-Frequency Cepstral Coefficients) and HMM (Hidden Markov Models) was introduced in this experiment, which gives promising results of 99.33% accuracy, when testing 25% of realizations (randomly selected from 100) identifying between 50 users/models. The experiment was repeated for different training/testing configurations and cross-validated, so this first approach could be a good starting point for next research including feature selection algorithms, biometric authentication score normalization, different audio & keyboard setup tests, etc

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

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    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

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    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

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    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
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