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ATHENA: An Ontology-Driven System for Natural Language Querying over Relational Data Stores.

, , , , , and . Proc. VLDB Endow., 9 (12): 1209-1220 (2016)

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Multilingual and code-switching ASR challenges for low resource Indian languages., , , , , , , , , and 12 other author(s). CoRR, (2021)Optimizing Interpretation Generation in Natural Language Query Answering for Real Time End Users., , , and . COMAD/CODS, page 341-349. ACM, (2021)Adaptive Discounting of Implicit Language Models in RNN-Transducers., , , , , and . ICASSP, page 8122-8126. IEEE, (2022)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)An Ontology based Dialog Interface to Database., , , and . SIGMOD Conference, page 1749-1752. ACM, (2018)Improving RNN-Transducers with Acoustic LookAhead., , , and . CoRR, (2023)Representation based meta-learning for few-shot spoken intent recognition., , , , , and . CoRR, (2021)Low Resource ASR: The Surprising Effectiveness of High Resource Transliteration., , , , , and . Interspeech, page 1529-1533. ISCA, (2021)Representation Based Meta-Learning for Few-Shot Spoken Intent Recognition., , , , , and . INTERSPEECH, page 4283-4287. ISCA, (2020)