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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 – 11 of 11 1 Language Models are Few-shot Multilingual Learners ... Winata, Genta Indra; Madotto, Andrea; Lin, Zhaojiang. - : arXiv, 2021 BASE Show details 2 BiToD: A Bilingual Multi-Domain Dataset For Task-Oriented Dialogue Modeling ... Lin, Zhaojiang; Madotto, Andrea; Winata, Genta Indra. - : arXiv, 2021 BASE Show details 3 Are Multilingual Models Effective in Code-Switching? ... Winata, Genta Indra; Cahyawijaya, Samuel; Liu, Zihan. - : arXiv, 2021 BASE Show details 4 Zero-Shot Dialogue State Tracking via Cross-Task Transfer ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Cho, Eunjoon; Crook, Paul. - : Underline Science Inc., 2021 BASE Show details 5 XPersona: Evaluating Multilingual Personalized Chatbot ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Zihan; Bang, Yejin. - : Underline Science Inc., 2021 BASE Show details 6 Learning Fast Adaptation on Cross-Accented Speech Recognition ... Winata, Genta Indra; Cahyawijaya, Samuel; Liu, Zihan. - : arXiv, 2020 BASE Show details 7 XPersona: Evaluating Multilingual Personalized Chatbot ... Lin, Zhaojiang; Liu, Zihan; Winata, Genta Indra. - : arXiv, 2020 BASE Show details 8 Meta-Transfer Learning for Code-Switched Speech Recognition ... Winata, Genta Indra; Cahyawijaya, Samuel; Lin, Zhaojiang; Liu, Zihan; Xu, Peng; Fung, Pascale. - : arXiv, 2020 Abstract: An increasing number of people in the world today speak a mixed-language as a result of being multilingual. However, building a speech recognition system for code-switching remains difficult due to the availability of limited resources and the expense and significant effort required to collect mixed-language data. We therefore propose a new learning method, meta-transfer learning, to transfer learn on a code-switched speech recognition system in a low-resource setting by judiciously extracting information from high-resource monolingual datasets. Our model learns to recognize individual languages, and transfer them so as to better recognize mixed-language speech by conditioning the optimization on the code-switching data. Based on experimental results, our model outperforms existing baselines on speech recognition and language modeling tasks, and is faster to converge. ... : Accepted in ACL 2020. The first two authors contributed equally to this work ... 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.2004.14228 https://arxiv.org/abs/2004.14228 BASE Hide details 9 On the Importance of Word Order Information in Cross-lingual Sequence Labeling ... Liu, Zihan; Winata, Genta Indra; Cahyawijaya, Samuel. - : arXiv, 2020 BASE Show details 10 Attention-Informed Mixed-Language Training for Zero-shot Cross-lingual Task-oriented Dialogue Systems ... Liu, Zihan; Winata, Genta Indra; Lin, Zhaojiang. - : arXiv, 2019 BASE Show details 11 Hierarchical Meta-Embeddings for Code-Switching Named Entity Recognition ... Winata, Genta Indra; Lin, Zhaojiang; Shin, Jamin. - : arXiv, 2019 BASE Show details

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