Background Older adults often have increasing memory problems (amnesia), and approximately 50 million people worldwide have dementia. This syndrome gradually affects a patient over a period of 10-20 years. Intelligent virtual agents may support people with amnesia. Objective This study aims to identify state-of-the-art experimental studies with virtual agents on a screen capable of verbal dialogues with a target group of older adults with amnesia. Methods We conducted a systematic search of PubMed, SCOPUS, Microsoft Academic, Google Scholar, Web of Science, and CrossRef on virtual agent and amnesia on papers that describe such experiments. Search criteria were ( Virtual Agent OR Virtual Assistant OR Virtual Human OR Conversational Agent OR Virtual Coach OR Chatbot ) AND ( Amnesia OR Dementia OR Alzheimer OR Mild Cognitive Impairment ). Risk of bias was evaluated using the QualSyst tool (University of Alberta), which scores 14 study quality items. Eligible studies are reported in a table including country, study design type, target sample size, controls, study aims, experiment population, intervention details, results, and an image of the agent. Results A total of 8 studies was included in this meta-analysis. The average number of participants in the studies was 20 (SD 12). The verbal interactions were generally short. The usability was generally reported to be positive. The human utterance was seen in 7 (88%) out of 8 studies based on short words or phrases that were predefined in the agent’s speech recognition algorithm. The average study quality score was 0.69 (SD 0.08) on a scale of 0 to 1. Conclusions The number of experimental studies on talking about virtual agents that support people with memory problems is still small. The details on the verbal interaction are limited, which makes it difficult to assess the quality of the interaction and the possible effects of confounding parameters. In addition, the derivation of the aggregated data was difficult. Further research with extended and prolonged dialogues is required.
Automatic translation allows people around the globe to communicate with one another. However, state-of-the art machine translation is still unable to capture fine-grained meaning. This paper introduces the idea of using Web image selections in text-to-text translation, specifically for lacunae, which are words that do not have a translation in another language. We asked human professional translators to rank Google translate translations of lacunae in German and Dutch. We then compared that ranking with a ranking based on color histograms of Web image data of the words. We found there is viable potential in the idea of using images to address lacunae in the field of machine translation. We publicly release a dataset and our code for others to explore this potential. Finally, we provide an outlook on research directions that would allow this idea to be used in practice.
BACKGROUND Older adults often have increasing memory problems, and worldwide about 50 million people have dementia. This syndrome gradually affects a patient over a period of 10-20 years. Intelligent virtual agents may support people suffering from memory problems. OBJECTIVE To identify the state of the art of experimental studies with virtual agents on a screen capable of verbal dialogues with older adults with memory problems. METHODS Conduct a systematic search into selected databases PubMed, SCOPUS, Microsoft Academic, Google Scholar, Web of Science and CrossRef on Virtual Agent and Memory Problems on papers that describe such experiments. Search criteria were (“Virtual Agent” OR “Virtual Assistant” OR “Virtual Human” OR “Conversational Agent” OR “Virtual Coach” OR Chatbot) AND (Dementia OR Alzheimer OR Amnesia OR “Mild Cognitive Impairment”). Risk of bias has been evaluated using the QualSyst tool that scores 14 study quality items. Eligible studies are reported in a table including country, study design type, target sample size, controls, study aims, experiment population, intervention details, results and an image of the agent. RESULTS Nine studies were included. The average number of participants in the studies was 18 (SD=12). The verbal interactions were generally short. The human utterance consisted in 8 out of 9 studies out of short words or phrases that were predefined in the agent’s speech recognition algorithm. The average study quality score was .68 (SD=.08) on a scale 0-1.The number of experimental studies on talking virtual agents that support people with memory problems is still small. The details on the verbal interaction are limited, which make it difficult to assess the quality of that interaction and the possible effect of confounding parameters. Further research is needed with extended and prolonged dialogues. CONCLUSIONS The number of experimental studies on talking virtual agents that support people with memory problems is still small. The details on the verbal interaction are limited, which make it difficult to assess the quality of that interaction and the possible effect of confounding parameters. Further research is needed with extended and prolonged dialogues.
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