Vistaar: Diverse Benchmarks and Training Sets for Indian Language ASR

Improving ASR systems is necessary to make new LLM-based use-cases accessible to people across the globe. In this paper, we focus on Indian languages, and make the case that diverse benchmarks are required to evaluate and improve ASR systems for Indian languages. To address this, we collate Vistaar as a set of 59 benchmarks across various language and domain combinations, on which we evaluate 3 publicly available ASR systems and 2 commercial systems. We also train IndicWhisper models by fine-tuning the Whisper models on publicly available training datasets across 12 Indian languages totalling to 10.7K hours. We show that IndicWhisper significantly improves on considered ASR systems on the Vistaar benchmark. Indeed, IndicWhisper has the lowest WER in 39 out of the 59 benchmarks, with an average reduction of 4.1 WER. We open-source all datasets, code and models.Comment: Accepted in INTERSPEECH 202

Modelling a pandemic with asymptomatic patients, impact of lockdown and herd immunity, with applications to SARS-CoV-2

The SARS-CoV-2 is a type of coronavirus that has caused the pandemic known as the Coronavirus Disease of 2019, or COVID-19. In traditional epidemiological models such as SEIR (Susceptible, Exposed, Infected, Removed), the exposed group E does not infect the susceptible group S. A distinguishing feature of COVID-19 is that, unlike with previous viral diseases, there is a distinct “asymptomatic” group A, which does not show any symptoms, but can nevertheless infect others, at the same rate as infected symptomatic patients. This situation is captured in a model known as SAIR (Susceptible, Asymptomatic, Infected, Removed), introduced in Robinson and Stillianakis (2013). The dynamical behavior of the SAIR model is quite different from that of the SEIR model. In this paper, we use Lyapunov theory to establish the global asymptotic stabililty of the SAIR model, both without and with vital dynamics. Then we develop compartmental SAIR models to cater to the migration of population across geographic regions, and once again establish global asymptotic stability. Next, we go beyond long-term asymptotic analysis and present methods for estimating the parameters in the SAIR model. We apply these estimation methods to data from several countries including India, and demonstrate that the predicted trajectories of the disease closely match actual data. We show that “herd immunity” (defined as the time when the number of infected persons is maximum) can be achieved when the total of infected, symptomatic and asymptomatic persons is as low as 25% of the population. Previous estimates are typically 50% or higher. We also conclude that “lockdown” as a way of greatly reducing inter-personal contact has been very effective in checking the progress of the disease. © 2020 The Author(s

Modelling the COVID-19 Pandemic: Asymptomatic Patients, Lockdown and Herd Immunity

The SARS-Cov-2 is a type of coronavirus that has caused the COVID-19 pandemic. In traditional epidemiological models such as SEIR (Susceptible, Exposed, Infected, Removed), the exposed group E does not infect the susceptible group S. A distinguishing feature of COVID-19 is that, unlike with previous viruses, there is a distinct "asymptomatic"group A, who do not show any symptoms, but can nevertheless infect others, at the same rate as infected patients. This situation is captured in a model known as SAIR (Susceptible, Asymptomatic, Infected, Removed), introduced in Robinson and Stilianakis (2013). The dynamical behavior of the SAIR model is quite different from that of the SEIR model. In this paper, we use Lyapunov theory to establish the global asymptotic stabiilty of the SAIR model. Next, we present methods for estimating the parameters in the SAIR model. We apply these estimation methods to data from several countries including India, and show that the predicted trajectories of the disease closely match actual data. ©2020 The Authors.This is an open access article under the CC BY-NC-ND license

Spinal Tuberculosis with Paraplegia in Pregnancy: a Case Report with Management of Spinal TB in Pregnancy

Spinal tuberculosis leading to paraplegia is uncommon in pregnancy and is a diagnostic and therapeutic challenge. We report a case of tubercular paraplegia presenting at 35 weeks of gestation. She was managed with Anti-tubercular drugs and did not require surgical intervention. Her neurological status improved and she was allowed to go in labour. She delivered a healthy term infant by cesarean. At three months follow-up, both mother and child are doing well.  Keywords: paraplegia; pregnancy; spinal tuberculosis

Vernal Keratoconjunctivitis- A Survey on Practice Patterns and Perspectives of Indian Ophthalmologists

Introduction: Vernal Keratoconjunctivitis (VKC) is a common chronic allergic condition mostly affecting children and their childhood. At present, the choice of medication varies greatly for the same severity of disease from one ophthalmologist to another. A standardised grading system and a comprehensive approach towards VKC including Quality of Life (QOL) assessment is the need of the hour. Aim: To learn the practice patterns and perspectives of Indian Ophthalmologists in the management of VKC and to propose strategies for the holistic approach. Materials and Methods: A cross-sectional survey was conducted in July 2020. A semi-structured questionnaire was sent via Google form to 200 ophthalmologists. Statistical analysis used: Data was entered in excel and analysis was performed using the Statistical Package of Social Sciences (SPSS) software version 20. Results: Out of 200 ophthalmologists, 146 (73%) participated in the survey. Among the participants, 43.8% used combination therapy in the management of VKC and 68.5% resorted to steroid therapy in severe cases. Tacrolimus (0.03%) was the most preferred immunomodulator among 56% ophthalmologists and only 11% assessed QOL in the patients periodically. Conclusion: Majority (around 2/3rd) felt immunotherapy and vitamin D supplementation can be tried in the management of VKC and there was a consensus on administering a QOL questionnaire in all patients with VKC in future which would provide holistic care

Dual-Sided Involvement of Energy Optimization and Strategic Bidding in Wind-PV System to Maximize Benefits for Customers and Power Providers

Global warming is causing industrial development to increase greenhouse gas emissions, impact power provider economies, and potentially pose a solution through renewable energy. In order to solve these issues, the research offers a dual strategic auction difficulty for renewable energy market clear prices (MCPs) to maximize supplier and buyer revenues while mitigating rival unpredictability and renewable vacillation power supply sources. The study uses scenario reduction techniques, including Beta and Weibull distribution of probability, forward-reduction technique, and underestimation and overestimation of the cost function to manage uncertainties in renewable energy. The Gravitation Search algorithm and a hybrid approach ordered weighted average distance (OWAD) combined, with Topsis operational gravitational search algorithm TOGSA (OWAD-TOGSA), are used to solve the multi-objective issue. The study evaluates the performance of IEEE standard 30-bus and 57-bus test systems and an Indian 75-bus operational system to solve a problem involving wind and sun energy in spite of its volatility. The proposed bidding approach is feasible and could increase revenue by nearly 10 %, potentially improving efficiency for electric energy-producing utilities and consumers, and its findings will be beneficial for similar research using optimization techniques

Study on impact of air pollution on asthma among school going children residing in urban Agra

Background: Air pollution is one of the world's most serious environmental problems. Air pollution has many negative health effects on the general population, especially children, individuals with underlying chronic disease, and the elderly. The aims of this study were to evaluate the effects of traffic-related pollution on the exacerbation of asthma and development of respiratory infections in schoolgoing children in Agra, suffering from asthma compared with healthy subjects, and to estimate the association between incremental increases in principal pollutants and the incidence of respiratory symptoms. Materials and Methods: We enrolled 702 children aged 6–18 years in this prospective study. A total of 342 children with asthma and 360 healthy subjects were monitored for 6 months from September 2013 to February 2014. Clinical data were combined with the results obtained using an air pollution monitoring system of the five most common pollutants. A total of 328 children with asthma and 345 healthy subjects completed follow-up. Results: Children with asthma reported significantly more days of fever (P <0.001) and cough (P < 0.001), episodes of rhinitis (P = 0.087), asthma attacks (P < 0.001), episodes of pneumonia (P < 0.003), and hospitalizations (P = 0.01). In the asthma cohort, living close to the street with a high traffic density was a risk factor for asthma exacerbations (odds ratio [OR] = 1.79; 95% confidence interval [CI], 1.13–2.84), whereas living near green areas was found to be protective (OR = 0.50; 95% CI, 0.31–0.80). Conclusion: There is a significant association between traffic-related pollution and the development of asthma exacerbations and respiratory infections in children suffering from asthma. These findings suggest that environmental control may be crucial for respiratory health in children with the underlying respiratory disease

Improvements in essential newborn care and newborn resuscitation services following a capacity building and quality improvement program in three districts of Uttar Pradesh, India

Background: Neonatal death remains a global challenge contributing to 45% of underfive deaths. With rising institutional delivery, to accelerate decline in neonatal mortality rate (NMR) improvement in the quality of perinatal care requires attention. Objectives: This implementation research targeted improving service delivery readiness for quality of newborn care at public health facilities in three districts of Uttar Pradesh, India, with high NMR. Materials and Methods: This before-after study assessed the facility readiness and quality of newborn services at 42 health facilities. The changes in 26 signal functions for routine and emergency obstetric and newborn care were tracked. Results: There was marked improvement in newborn service availability: skilled birth attendants (51%), resuscitation (30%), and kangaroo mother care (27%) at these facilities. A multifold rise in newborn resuscitation efforts and documentation (n = 4431 vs. n = 144 in preintervention period) with high success rate (98.6%) was observed. There was also improvement in obstetric care services including partograph use (31%) and active management of third stage of labor (46%). However, several infrastructural indicators (electricity, water supply, toilets, and sanitation) remained unchanged. Conclusion: Overall improvements were observed in the majority of the signal functions for perinatal care and newborn resuscitation efforts. There was a limited impact on the infrastructural and supervision components