Phyloepidemiology and adaptive evolution of SARS-CoV2 during the first and second wave of COVID-19 in India

Introduction. This study aimed to identify the circulating lineages of SARS-CoV-2, prevalent mutations in these lineages, and the selective pressure on the genome of SARS-CoV-2 during the first and second waves of the COVID-19 pandemic in India. Methods. We downloaded 1,451 sequences from June 2020 to June 2021 from the National Center for Biotechnology Information (NCBI) and the Global Initiative on Sharing All Influenza Database (GISAID). We identified the lineages using the Pangolin COVID-19 lineage assigner. Results. We found 41 circulating lineages in India during the year studied. Thirty-five lineages were circulating during the first wave and twenty during the second wave, including six new lineages. During the first wave in 2020, only one Variant of Concern (Alpha) was found, but during the second wave in 2021, three Variants of Concern (Alpha, Beta, and Delta) were in circulation, as well as one Variant Under Monitoring. The most frequent mutations observed were S: D614G, NSP3: F106F, NSP12b: P314L, ORF3a: Q57H, M: Y71Y, NSP14:C279C, S: D294D, and N: S194L. The ten most mutated samples all belonged to the Delta variant of B.1.617.2 lineage and were found in the second wave. Five mutations in the spike protein (L452R, T478K, E484Q, N501Y, and D614G), responsible for increased transmissibility and reduced neutralization by convalescent sera, were majorly prevalent during the second wave. D614G, L452R, and T478K were present at prevalence rates of 88.25%, 21.04%, and 16.80%, respectively. The major selection was purifying selection, but a few sites in the NSP2, NSP3, NSP13, S protein, ORF3a, and ORF9 evolved under positive selection. Conclusion. We report six novel mutations (three in NSP2 [P129A, V381A, V381F], one in NSP3 [P822S], and one in the S protein [Q23R]) that evolved under positive selection pressure

SPRING: speech and pronunciation improvement through games, for Hispanic children

Lack of proper English pronunciations is a major problem for immigrant population in developed countries like U.S. This poses various problems, including a barrier to entry into mainstream society. This paper presents a research study that explores the use of speech technologies merged with activity-based and arcade-based games to do pronunciation feedback for Hispanic children within the U.S. A 3-month long study with immigrant population in California was used to investigate and analyze the effectiveness of computer aided pronunciation feedback through games. In addition to quantitative findings that point to statistically significant gains in pronunciation quality, the paper also explores qualitative findings, interaction patterns and challenges faced by the researchers in dealing with this community. It also describes the issues involved in dealing with pronunciation as a competency.Comment: ACM ICTD 201

Speech-enabled Systems for Language Learning

Levels of literacy and the variance in them, continue to be a problem in the world. These problems are ubiquitous in the sense that they change form from developing to developed regions, but do not seize to exist. For example, while teacher absenteeism is a fairly large problem in the developing world, student motivation can pose challenges in the developed world. Prior research has demonstrated that games can serve as an efficient medium in bridging these literacy gaps, generating student motivation (or engagement) not just in short term but also in the long term. This dissertation is dedicated to the investigation and application of spoken language technology to language acquisition contexts in the developed world. We explore the broader research question in two major contexts.Firstly, lack of proper English pronunciations is a major problem for immigrant population in developed countries like U.S. This poses various problems, including a barrier to entry into mainstream society. Therefore, the first part of the dissertation involves exploration of speech technologies merged with activity-based and arcade-based games to do pronunciation feedback for Hispanic children. This also involves using linguistic theory to determine computational criteria for intelligibility in speech and computational adaptations to reflect them. We also present results from a 3-month long evaluation of this system. Secondly, a large body of research has shown that the literacy gap between children is well-established before formal schooling begins, and predicts academic performance throughout primary, middle and secondary school. Therefore, in the second part of the dissertation we explore natural interactions for preschoolers that would engage them in game-like activities that involve short follow-up conversations. We explore the design and implementation of a conversational agent called Spot, that acts as a question-answering companion for preschool children. We present a month long study with 20 preschoolers with some insight on the potential, efficiency and usage of such a system. We end with a discussion on computational complexities in building Spot, and rules that it uses to work around speech recognition and natural language understanding errors

Improving Literacy in Developing Countries Using Speech Recognition-Supported Games on Mobile Devices

Learning to read in a second language is challenging, but highly rewarding. For low-income children in developing countries, this task can be significantly more challenging because of lack of access to high-quality schooling, but can potentially improve economic prospects at the same time. A synthesis of research findings suggests that practicing recalling and vocalizing words for expressing an intended meaning could improve word reading skills – including reading in a second language – more than silent recognition of what the given words mean. Unfortunately, many language learning software do not support this instructional approach, owing to the technical challenges of incorporating speech recognition support to check that the learner is vocalizing the correct word. In this paper, we present results from a usability test and two subsequent experiments that explore the use of two speech recognitionenabled mobile games to help rural children in India read words with understanding. Through a working speech recognition prototype, we discuss two major contributions of this work: first, we give empirical evidence that shows the extent to which productive training (i.e. vocalizing words) is superior to receptive vocabulary training, and discuss the use of scaffolding hints to “unpack ” factors in the learner‟s linguistic knowledge that may impact reading. Second, we discuss what our results suggest for future research in HCI. Author Keywords Educational games; developing countries; information an