ABSTRACT
During the COVID-19 pandemic, many research areas that require in person experiments with human volunteers have been impacted due to lockdowns and other activity-restricting policies. The field of robotics is no exception, and specially human-robot interaction research has been severely impacted. In order to circumvent the difficulty of gathering volunteers in person to interact with a robot, we have decided to build a novel crowdsourcing web platform for hosting our "Talk to Kotaro"experiment. The experiment consists of volunteers talking to a robot avatar and reacting to its semantic-free utterances. The developed web platform, which was built using the Python Flask framework, allows for such interactions while recording audio and video and other relevant data, which will be used for studying human impression estimation on gibberish speech. This paper describes not only the experiment and its preliminary results, but the developed platform itself;such tool is essential during pandemics and very useful for regular times, because it enables crowdsourcing data from all over the world. © 2022 IEEE.
ABSTRACT
The policies that countries develop to face the crisis generated by the COVID-19 pandemic have a strong impact on the impact it causes. In Cuba, the general strategy to confront the pandemic was directed by the government, which, under the guidance of the Ministry of Public Health, drew up an action plan based on stages and phases to comply with the strategy, taking into account the evolution of the disease in the country. The objective of this research is to assess the effectiveness of the government strategy for the treatment of the COVID-19 disease in Cuba, based on the analysis of the integration of the different organizations that participated. The analysis carried out allowed us to find the interrelationships between the different organizations involved with influences in the treatment of the pandemic. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.