Papers by Mirco Ravanelli
TARIC-SLU: A Tunisian Benchmark Dataset for Spoken Language Understanding (2024.lrec-main)
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| Challenge: | Existing SLU resources are limited in high-resource languages such as English, Mandarin and French. |
| Approach: | They propose to use a Tunisian dialect dataset to build a semantic model of the system that is continuously annotated with dialogue acts and slots. |
| Outcome: | The proposed dataset is based on train-based and ASR-based models of train-driven conversations in Tunisian dialect. |
Adaptation Odyssey in LLMs: Why Does Additional Pretraining Sometimes Fail to Improve? (2024.emnlp-main)
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| Challenge: | In the last decade, the generalization and adaptation abilities of deep learning models were evaluated on fixed training and test distributions. |
| Approach: | They propose to train large language models on unlabeled text corpora and train them online. |
| Outcome: | The proposed model training on a text domain could degrade its perplexity on the test portion of the same domain. |