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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 10 of 10 1 Predicting the Performance of Multilingual NLP Models ... Srinivasan, Anirudh; Sitaram, Sunayana; Ganu, Tanuja. - : arXiv, 2021 BASE Show details 2 Multilingual and code-switching ASR challenges for low resource Indian languages ... Diwan, Anuj; Vaideeswaran, Rakesh; Shah, Sanket. - : arXiv, 2021 BASE Show details 3 On the Universality of Deep Contextual Language Models ... Bhatt, Shaily; Goyal, Poonam; Dandapat, Sandipan. - : arXiv, 2021 BASE Show details 4 A Survey of Code-switching: Linguistic and Social Perspectives for Language Technologies ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Bullock, Barbara; Sitaram, Sunayana. - : Underline Science Inc., 2021 BASE Show details 5 GLUECoS : An Evaluation Benchmark for Code-Switched NLP ... Khanuja, Simran; Dandapat, Sandipan; Srinivasan, Anirudh. - : arXiv, 2020 BASE Show details 6 A New Dataset for Natural Language Inference from Code-mixed Conversations ... Khanuja, Simran; Dandapat, Sandipan; Sitaram, Sunayana. - : arXiv, 2020 BASE Show details 7 Learning not to Discriminate: Task Agnostic Learning for Improving Monolingual and Code-switched Speech Recognition ... Madhumani, Gurunath Reddy; Shah, Sanket; Abraham, Basil; Joshi, Vikas; Sitaram, Sunayana. - : arXiv, 2020 Abstract: Recognizing code-switched speech is challenging for Automatic Speech Recognition (ASR) for a variety of reasons, including the lack of code-switched training data. Recently, we showed that monolingual ASR systems fine-tuned on code-switched data deteriorate in performance on monolingual speech recognition, which is not desirable as ASR systems deployed in multilingual scenarios should recognize both monolingual and code-switched speech with high accuracy. Our experiments indicated that this loss in performance could be mitigated by using certain strategies for fine-tuning and regularization, leading to improvements in both monolingual and code-switched ASR. In this work, we present further improvements over our previous work by using domain adversarial learning to train task agnostic models. We evaluate the classification accuracy of an adversarial discriminator and show that it can learn shared layer parameters that are task agnostic. We train end-to-end ASR systems starting with a pooled model that uses ... : 5 pages (4 pages + 1 reference), 3 tables, 2 figures ... Keyword: Audio and Speech Processing eess.AS; Computation and Language cs.CL; FOS Computer and information sciences; FOS Electrical engineering, electronic engineering, information engineering; Sound cs.SD URL: https://dx.doi.org/10.48550/arxiv.2006.05257 https://arxiv.org/abs/2006.05257 BASE Hide details 8 Cross-lingual and Multilingual Spoken Term Detection for Low-Resource Indian Languages ... Shah, Sanket; Guha, Satarupa; Khanuja, Simran. - : arXiv, 2020 BASE Show details 9 Phone Merging for Code-switched Speech Recognition Sivasankaran, Sunit; Srivastava, Brij Mohan Lal; Sitaram, Sunayana... In: Third Workshop on Computational Approaches to Linguistic Code-switching ; https://hal.inria.fr/hal-01800466 ; Third Workshop on Computational Approaches to Linguistic Code-switching, collocated with ACL 2018 Jul 2018, Melbourne, Australia (2018) BASE Show details 10 Polyglot Neural Language Models: A Case Study in Cross-Lingual Phonetic Representation Learning ... Tsvetkov, Yulia; Sitaram, Sunayana; Faruqui, Manaal. - : arXiv, 2016 BASE Show details

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