Papers by Dhanush Bekal
Text Generation from Knowledge Graphs with Graph Transformers (N19-1)
Copied to clipboard
| Challenge: | Existing methods for generating text with structured inputs are expensive and require manual annotation. |
| Approach: | They propose a graph transforming encoder which leverages relational structure of knowledge graphs without imposing linearization or hierarchical constraints. |
| Outcome: | The proposed system produces more informative texts than competing methods. |
AdaBERT-CTC: Leveraging BERT-CTC for Text-Only Domain Adaptation in ASR (2023.emnlp-industry)
Copied to clipboard
| Challenge: | End-to-end (E2E) automatic speech recognition models struggle to recognize out-of-domain words such as proper nouns and domain-specific terms. |
| Approach: | They propose a domain adaptation technique that relies solely on textual data to adapt to out-of-domain words. |
| Outcome: | The proposed method outperforms the base model by up to 14% relative word error rate improvement on several out-of-domain, publicly available datasets. |