Contains links to publications, dataset releases, reading resources, and other artifacts. For technology demos go to the Explore tab.

Publications

• Rajaa, S., 2023. Improving End-to-End SLU performance with Prosodic Attention and Distillation. In Interspeech 2023.
• Rajaa, S., Anandan, K., Dalmia, S., Gupta, T. and Chng, E.S., 2023, June. Improving Spoken Language Identification with Map-Mix. In ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 1-5). IEEE.
• Sahu, S.K. and Dalmia, S., 2022. On The Diversity of ASR Hypotheses In Spoken Language Understanding. In I Can’t Believe It’s Not Better Workshop: Understanding Deep Learning Through Empirical Falsification.
• Surya Kant Sahu. 2022. TaskMix: Data Augmentation for Meta-Learning of Spoken Intent Understanding. In Findings of the Association for Computational Linguistics: AACL-IJCNLP 2022, pages 67–72, Online only. Association for Computational Linguistics.
• Karthik Ganesan, Pakhi Bamdev, Jaivarsan B, Amresh Venugopal, and Abhinav Tushar. 2021. N-Best ASR Transformer: Enhancing SLU Performance using Multiple ASR Hypotheses. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers), pages 93–98, Online. Association for Computational Linguistics.

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Datasets

• Emotional TTS dataset release by Swaraj Dalmia, Kaustav Tamuly, Pulkit Mishra, Shangeth Raaja, Kumarmanas Nethil & Abhinav Tushar
• Phone Number Entity Dataset by Kumarmanas Nethil, Anirudh Thatipelli & Sachin Kumar
• Speech to Intent Dataset by Kumarmanas Nethil, Kriti Anandan, & Unnati Senani

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Library

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Projects

Here is a selection of projects from our GitHub portfolio. Subscribe to our blog to stay updated on upcoming items.

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