Papers by Chayan Sarkar
tagE: Enabling an Embodied Agent to Understand Human Instructions (2023.findings-emnlp)
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| Challenge: | Existing systems for natural language understanding (NLU) are limited due to the inherent ambiguity and incompleteness inherent in natural language. |
| Approach: | They propose a system to extract tasks from natural language instructions and map them to robots' established collection of skills. |
| Outcome: | The proposed system outperforms baseline models in the training and evaluation of a dataset featuring complex instructions. |
Can Visual Context Improve Automatic Speech Recognition for an Embodied Agent? (2022.emnlp-main)
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| Challenge: | ASR systems are often unable to recognize speech due to generic datasets and open-vocabulary modeling. |
| Approach: | They propose to incorporate a robot’s visual information into an ASR system and improve the recognition of a spoken utterance containing a visible entity. |
| Outcome: | The proposed method achieves a 59% relative reduction in WER from an unmodified ASR system. |