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1.
4th International Conference on Computer and Applications, ICCA 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2249049

ABSTRACT

We propose an Arabic talking face called Badr to teach the language vocabulary for young students under COVID-19 pandemic. Badr is built on the previous talking face Baldi (e.g., an American English talking face) with many enhancements in interaction and words pronunciation. It can complement the work of instructors who can get tired and bored when teaching online for long hours. It can pronounce standard Arabic vocabulary accurately and interact with learners in natural manner. Listening and observing Badr improve the learners' ability to understand speech in a noisy background. We tested Badr with Qatar University students, and we show its effectiveness and usefulness in introducing smoothly new vocabulary. Badr can act as an independent tutor for different categories of learners including those with learning difficulties, slow learners, and non-Arabic speaking learners. © 2022 IEEE.

2.
2021 IEEE Global Conference on Artificial Intelligence and Internet of Things, GCAIoT 2021 ; : 112-117, 2021.
Article in English | Scopus | ID: covidwho-1769584

ABSTRACT

Social media platforms have become one of the most powerful tools for organizations and individuals to publish news and express thoughts or feelings. With the increasingly enormous number of internet users in Saudi Arabia, the need raised to analyze Arabic posts. Since the emergence of COVID-19 in the latest 2019, it lefts economies and businesses counting the cost while governments fight the spread of the virus with new compartmentalization measures. Keeping in view the importance of quick and timely data analysis and sharing for policy actions, Artificial intelligence (AI) has played a crucial role in facilitating the exchange of views and information between scientists and decision-makers during the Coronavirus pandemic, and they continue to do so. This work mined to these content-related tweets to see how people's feelings and expressions are changing. The results of this analysis can be used with integration with several IoT technologies to reduce the impact of covid-19 and drive new decisions in this field. For this goal, we proposed a Machine Learning (ML) models that can classify both of the sentiment and topic of Modern Standard Arabic (MSA) tweets and achieve high accuracy results. © 2021 IEEE.

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