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Optimizing Interpretation Generation in Natural Language Query Answering for Real Time End Users.

, , , and . COMAD/CODS, page 341-349. ACM, (2021)

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Adaptive Discounting of Implicit Language Models in RNN-Transducers., , , , , and . ICASSP, page 8122-8126. IEEE, (2022)Optimizing Interpretation Generation in Natural Language Query Answering for Real Time End Users., , , and . COMAD/CODS, page 341-349. ACM, (2021)Natural Language Querying of Complex Business Intelligence Queries., , , , , , , , and . SIGMOD Conference, page 1997-2000. ACM, (2019)Speech-enriched Memory for Inference-time Adaptation of ASR Models to Word Dictionaries., , , , and . EMNLP, page 14820-14835. Association for Computational Linguistics, (2023)Soft Random Sampling: A Theoretical and Empirical Analysis., , , , , and . CoRR, (2023)Partitioned Gradient Matching-based Data Subset Selection for Compute-Efficient Robust ASR Training., , , , and . EMNLP (Findings), page 5999-6010. Association for Computational Linguistics, (2022)Functional Partitioning of Ontologies for Natural Language Query Completion in Question Answering Systems., , , and . IJCAI, page 4331-4337. ijcai.org, (2018)Representation based meta-learning for few-shot spoken intent recognition., , , , , and . CoRR, (2021)Bootstrapping Chatbot Interfaces to Databases., , , , , and . COMAD/CODS, page 47-55. ACM, (2021)Unified Semantic Parsing with Weak Supervision., , , , , and . ACL (1), page 4801-4810. Association for Computational Linguistics, (2019)