The Life of an Indigenous Youth

Being an Indigenous youth can provide a world full of opportunities as well as serve as a barrier. Youth hold the power to shift the dynamics of the world. If we want change, we must provide leadership support for youth to make change possible. Indigenous youth, in particular, continue to face racism and discrimination and are marginalized in society, but when they have a sense of belonging and a strong cultural identity, they become resilient, powerful individuals. They have roots through their ancestral lineage, wisdom, and intelligence. They are the future leaders of their communities. It is critical to restore leadership from the erosion of their traditional knowledge practices and ancestral lands so that they can begin to create a more sustainable, interdependent system for the coming generations. I have had the privilege of meeting many other Newari and non-Newari people in my life, and this range of experiences has allowed me to understand my role in relation to my Indigenous community as well as in relation to the non-Indigenous world around me. There have been moments where I felt extremely supported and there have also been moments when I experienced clashes between my ideas and the ideas of my community. Each moment has taught me something and helped me understand the world around me. This chapter will showcase my experiences as an Indigenous youth in various sectors, primarily in the area of human rights

VENLAFAXINE AS AN AUGMENTATION OF ELECTRO- CONVULSIVE THERAPY IN TREATMENT RESISTANT DEPRESSION- A CASE REPORT

Treatment of challenging cases of Depression with or without psychotic features often needs use of Electro-convulsive Therapy at some stage. The purpose of this case report is to demonstrate the effectiveness of augmentation of Electro-convulsive Therapy, in treatment of a case of Resistant Depression with antidepressant medication, Venlafaxine. Though further research is needed to confirm that with ongoing Electro-convulsive Therapy, changing the antidepressant classes, SSRI or NaSSA to Venlafaxine will improve the recovery rate

ISLTranslate: Dataset for Translating Indian Sign Language

Sign languages are the primary means of communication for many hard-of-hearing people worldwide. Recently, to bridge the communication gap between the hard-of-hearing community and the rest of the population, several sign language translation datasets have been proposed to enable the development of statistical sign language translation systems. However, there is a dearth of sign language resources for the Indian sign language. This resource paper introduces ISLTranslate, a translation dataset for continuous Indian Sign Language (ISL) consisting of 31k ISL-English sentence/phrase pairs. To the best of our knowledge, it is the largest translation dataset for continuous Indian Sign Language. We provide a detailed analysis of the dataset. To validate the performance of existing end-to-end Sign language to spoken language translation systems, we benchmark the created dataset with a transformer-based model for ISL translation.Comment: Accepted at ACL 2023 Findings, 8 Page

Shapes of Emotions: Multimodal Emotion Recognition in Conversations via Emotion Shifts

Emotion Recognition in Conversations (ERC) is an important and active research area. Recent work has shown the benefits of using multiple modalities (e.g., text, audio, and video) for the ERC task. In a conversation, participants tend to maintain a particular emotional state unless some stimuli evokes a change. There is a continuous ebb and flow of emotions in a conversation. Inspired by this observation, we propose a multimodal ERC model and augment it with an emotion-shift component that improves performance. The proposed emotion-shift component is modular and can be added to any existing multimodal ERC model (with a few modifications). We experiment with different variants of the model, and results show that the inclusion of emotion shift signal helps the model to outperform existing models for ERC on MOSEI and IEMOCAP datasets.Comment: 13 pages, Accepted at Workshop on Performance and Interpretability Evaluations of Multimodal, Multipurpose, Massive-Scale Models, COLING 202

ScriptWorld: Text Based Environment For Learning Procedural Knowledge

Text-based games provide a framework for developing natural language understanding and commonsense knowledge about the world in reinforcement learning based agents. Existing text-based environments often rely on fictional situations and characters to create a gaming framework and are far from real-world scenarios. In this paper, we introduce ScriptWorld: a text-based environment for teaching agents about real-world daily chores and hence imparting commonsense knowledge. To the best of our knowledge, it is the first interactive text-based gaming framework that consists of daily real-world human activities designed using scripts dataset. We provide gaming environments for 10 daily activities and perform a detailed analysis of the proposed environment. We develop RL-based baseline models/agents to play the games in Scriptworld. To understand the role of language models in such environments, we leverage features obtained from pre-trained language models in the RL agents. Our experiments show that prior knowledge obtained from a pre-trained language model helps to solve real-world text-based gaming environments. We release the environment via Github: https://github.com/Exploration-Lab/ScriptWorldComment: Accepted at IJCAI 2023, 26 Pages (7 main + 19 for appendix

U-CREAT: Unsupervised Case Retrieval using Events extrAcTion

The task of Prior Case Retrieval (PCR) in the legal domain is about automatically citing relevant (based on facts and precedence) prior legal cases in a given query case. To further promote research in PCR, in this paper, we propose a new large benchmark (in English) for the PCR task: IL-PCR (Indian Legal Prior Case Retrieval) corpus. Given the complex nature of case relevance and the long size of legal documents, BM25 remains a strong baseline for ranking the cited prior documents. In this work, we explore the role of events in legal case retrieval and propose an unsupervised retrieval method-based pipeline U-CREAT (Unsupervised Case Retrieval using Events Extraction). We find that the proposed unsupervised retrieval method significantly increases performance compared to BM25 and makes retrieval faster by a considerable margin, making it applicable to real-time case retrieval systems. Our proposed system is generic, we show that it generalizes across two different legal systems (Indian and Canadian), and it shows state-of-the-art performance on the benchmarks for both the legal systems (IL-PCR and COLIEE corpora).Comment: Accepted at ACL 2023, 15 pages (12 main + 3 Appendix

Generalized Product-of-Experts for Learning Multimodal Representations in Noisy Environments

A real-world application or setting involves interaction between different modalities (e.g., video, speech, text). In order to process the multimodal information automatically and use it for an end application, Multimodal Representation Learning (MRL) has emerged as an active area of research in recent times. MRL involves learning reliable and robust representations of information from heterogeneous sources and fusing them. However, in practice, the data acquired from different sources are typically noisy. In some extreme cases, a noise of large magnitude can completely alter the semantics of the data leading to inconsistencies in the parallel multimodal data. In this paper, we propose a novel method for multimodal representation learning in a noisy environment via the generalized product of experts technique. In the proposed method, we train a separate network for each modality to assess the credibility of information coming from that modality, and subsequently, the contribution from each modality is dynamically varied while estimating the joint distribution. We evaluate our method on two challenging benchmarks from two diverse domains: multimodal 3D hand-pose estimation and multimodal surgical video segmentation. We attain state-of-the-art performance on both benchmarks. Our extensive quantitative and qualitative evaluations show the advantages of our method compared to previous approaches.Comment: 11 Pages, Accepted at ICMI 2022 Ora