Papers by Gwenaelle Cunha Sergio
Attentively Embracing Noise for Robust Latent Representation in BERT (2020.coling-main)
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| Challenge: | Modern digital personal assistants interact with users through voice . high error rates still prevail in the widespread adoption of speech technology . |
| Approach: | They propose to extract more robust latent representations for noisy ASR text classification using transformer tokens and attentive embracement layer and multi-head attention layer. |
| Outcome: | The proposed model significantly outperforms the baseline model on the Chatbot and Snips corpora for intent classification with ASR error. |