Is a Wizard-of-Oz Required for Robot-Led Conversation Practice in a Second Language?

The large majority of previous work on human-robot conversations in a second language has been performed with a human wizard-of-Oz. The reasons are that automatic speech recognition of non-native conversational speech is considered to be unreliable and that the dialogue management task of selecting robot utterances that are adequate at a given turn is complex in social conversations. This study therefore investigates if robot-led conversation practice in a second language with pairs of adult learners could potentially be managed by an autonomous robot. We first investigate how correct and understandable transcriptions of second language learner utterances are when made by a state-of-the-art speech recogniser. We find both a relatively high word error rate (41%) and that a substantial share (42%) of the utterances are judged to be incomprehensible or only partially understandable by a human reader. We then evaluate how adequate the robot utterance selection is, when performed manually based on the speech recognition transcriptions or autonomously using (a) predefined sequences of robot utterances, (b) a general state-of-the-art language model that selects utterances based on learner input or the preceding robot utterance, or (c) a custom-made statistical method that is trained on observations of the wizard’s choices in previous conversations. It is shown that adequate or at least acceptable robot utterances are selected by the human wizard in most cases (96%), even though the ASR transcriptions have a high word error rate. Further, the custom-made statistical method performs as well as manual selection of robot utterances based on ASR transcriptions. It was also found that the interaction strategy that the robot employed, which differed regarding how much the robot maintained the initiative in the conversation and if the focus of the conversation was on the robot or the learners, had marginal effects on the word error rate and understandability of the transcriptions but larger effects on the adequateness of the utterance selection. Autonomous robot-led conversations may hence work better with some robot interaction strategies.

Domestic component level analysis for multipurpose autonomous robot

Multipurpose autonomous robot technology has been developed to assist transportation sectors or the current emergency as the Covid-19 pandemic. A practical issue in the robotic industry concerns the domestic content in commodities, services, and a combination of goods and services commonly determined as domestic component level (DCL). To be considered a standardized national product, a product's DCL must surpass a certain level of local content composition. This research aims to investigate the DCL of a developed multipurpose autonomous robot in Indonesia called ROM20. The research was initiated by interviewing specialists in DCL calculation and robotics research to perform DCL analysis on ROM20. The next step was breaking down the ROM20 components into a second layer component, in which the amount of domestic component and overseas components can be derived. Finally, the ROM20 DCL value was calculated by dividing the cost of domestic components by the total cost of domestic and overseas components. As a digital product, the ROM20 DCL calculation result showed that the manufacturing aspect is 70 %, and the development aspect is 30 %. The overall ROM20 DCL value has been calculated as 52.23 %, which surpasses the national standard threshold at 40 % DCL value. Therefore, ROM20 can be considered a high-value standardized national product, impacting the competitiveness of local products and the fast-growing medical device industry in Indonesia.

Assistive Robots for Patients with ALS: An Exploratory Study with an Early Stage Demonstrator (Preprint)

BACKGROUND Although robotic manipulators have great potential in promoting motor independence of people with motor impairments, only few systems are currently commercially available. In addition to technical, economic and normative barriers, a key challenge for their diffusion is the current lack of evidence regarding usefulness, acceptance and user-specific requirements. OBJECTIVE Against this background, a semi-autonomous robot system was developed in the R&D project ROBINA to support people with amyotrophic lateral sclerosis (ALS) in various everyday activities. METHODS The developed early stage demonstrator was evaluated in a task-based laboratory study with eleven ALS patients. Based on a mixed-methods design consisting of standardized questionnaires, observation protocols, and semi-structured interviews, participants were asked about usability, acceptance, and design requirements. RESULTS The majority of the participants considered the system provide relevant support within the test scenarios and perceived it as easy to use. Technical requirements consisted in precise object manipulation, reliable autonomous robot actions, and an intuitive GUI. In addition, the adaptability of the system to the abilities and disease-related limitations of the users, as well as a higher degree of intervention in the control and autonomous robot actions, was highlighted. Finally, the need for a holistic concept of robotic assistance in order to adequately address user-specific needs, was emphasized. CONCLUSIONS In summary, it can be stated that robotic manipulators can contribute to the compensation of motor impairments and increase both the autonomy and the psychological well-being of those affected. In this context, further opportunities to relieve the burden on the care network can be expected, especially regarding repetitive actions. CLINICALTRIAL The study is registered in the German Clinical Trials Registry (DRKS00016554).

Study of Indoor Visual SLAM System for Semi-autonomous Robot Platform

This study propose the use of heterogeneous visual landmarks, points and line segments, to achieve effective cooperation in indoor SLAM environments. In order to achieve un-delayed initialization required by the bearing-only observations, the well-known inverse-depth parameterization is adopted to estimate 3D points. Similarly, to estimate 3D line segments, we present a novel parameterization based on anchored Plücker coordinates, to which extensible endpoints are added