Increase Apparent Public Speaking Fluency By Speech Augmentation

Fluent and confident speech is desirable to every speaker. But professional speech delivering requires a great deal of experience and practice. In this paper, we propose a speech stream manipulation system which can help non-professional speakers to produce fluent, professional-like speech content, in turn contributing towards better listener engagement and comprehension. We propose to achieve this task by manipulating the disfluencies in human speech, like the sounds 'uh' and 'um', the filler words and awkward long silences. Given any unrehearsed speech we segment and silence the filled pauses and doctor the duration of imposed silence as well as other long pauses ('disfluent') by a predictive model learned using professional speech dataset. Finally, we output a audio stream in which speaker sounds more fluent, confident and practiced compared to the original speech he/she recorded. According to our quantitative evaluation, we significantly increase the fluency of speech by reducing rate of pauses and fillers

Review—Non-Invasive Monitoring of Human Health by Exhaled Breath Analysis: A Comprehensive Review

Exhaled human breath analysis is a very promisingfield of research work having great potential for diagnosis of diseases in non-invasive way. Breath analysis has attracted huge attention in thefield of medical diagnosis and disease monitoring in the last twodecades. VOCs/gases (Volatile Organic Compounds) in exhaled breath bear thefinger-prints of metabolic and biophysicalprocesses going on in human body. It’s a non-invasive, fast, non-hazardous, cost effective, and point of care process for diseasestate monitoring and environmental exposure assessment in human beings. Some VOCs/gases in exhaled breath are bio-markers ofdifferent diseases and their presence in excess amount is indicative of un-healthiness. Breath analysis has the potential for earlydetection of diseases. However, it is still underused and commercial device is yet not available owing to multiferrious challenges.This review is intended to provide an overview of major biomarkers (VOCs/gases) present in exhaled breath, importance of theiranalysis towards disease monitoring, analytical techniques involved, promising materials for breath analysis etc. Finally, relatedchallenges and limitations along with future scope will be touched upon.will be touched upon

Essays on Impacts of Women Empowerment on the Health Outcomes of Children

Chapter 1: Taking cognizance of the lack of representation of women in politics, the Indian government in 1993, enacted the 73rd constitutional amendment which led to a sudden increase in the representation of women in the local governments. Exploiting the exogenous variation in the timing of implementation of the 73rd amendment across the states, I study the spillover effects of this mandated empowerment of women on the health outcomes of children by using nationally representative survey data and employing a difference-in-difference estimation strategy. In this study, I find evidence of a positive impact of mandated women empowerment on the survival outcomes of higher birth order children. I also find evidence of increased birth spacing as the possible mechanism through which the increased representation of women in the local government leads to the improvement in the survival outcomes of children. Findings also suggests that the reservation at all levels of the local government is not equally effective and is mainly driven by the increased representation of women at the village level. Chapter 2: In this paper, I investigate the impact of the change in the gender composition of politicians due to the improved electoral performance of women in state-level elections in India on the survival outcomes of children. Early childhood mortality in India has been a matter of concern as it is among the countries which report high neonatal and infant mortality. The lack of decent healthcare facilities coupled with the cultural and social norms which dictate the preference for boy children have led to inferior health outcomes for the higher birth-order children, especially girl children. In this paper, I postulate that an improvement in the representation of women in a male-dominated decision-making position leads to better healthcare infrastructure and policies and a reduction in bias against women stemming from social and cultural norms and thus improves the early childhood mortality outcomes of children. I use a health survey data consisting of information about the reproductive history of mothers who gave birth in the period 1990-to 2015 and combine it with the data on the electoral performance of women in state legislative assembly elections conducted within the period 1989-to 2014 to examine the impact of a change in the gender composition of politicians at the district level on the neonatal and infant survival outcomes of the children born within each election-cycle in the respective districts. To correct for the endogeneity concerns arising out of the unobserved voter preferences, I exploit the quasi-randomness of women’s victories in close men-women elections using a regression discontinuity design. In contrast to previous research, I find that a change in the gender composition of politicians at the district level does not have an overall impact on the survival outcomes of children. Contrary to previous research, the findings also suggest that only girl children of higher birth order experience an improved neonatal survival probability relative to boys

Automated Attribute Extraction from Legal Proceedings

The escalating number of pending cases is a growing concern world-wide. Recent advancements in digitization have opened up possibilities for leveraging artificial intelligence (AI) tools in the processing of legal documents. Adopting a structured representation for legal documents, as opposed to a mere bag-of-words flat text representation, can significantly enhance processing capabilities. With the aim of achieving this objective, we put forward a set of diverse attributes for criminal case proceedings. We use a state-of-the-art sequence labeling framework to automatically extract attributes from the legal documents. Moreover, we demonstrate the efficacy of the extracted attributes in a downstream task, namely legal judgment prediction.Comment: Presented in Mining and Learning in the Legal Domain (MLLD) workshop 202