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README.md
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---
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# End-to-end SLU model for Timers and Such
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Attention-based RNN sequence-to-sequence model for [Timers and Such](https://arxiv.org/abs/2104.01604) trained on the `train-real` subset. This model checkpoint achieves 86.7% accuracy on `test-real`.
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year = {2021},
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publisher = {GitHub},
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journal = {GitHub repository},
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howpublished = {
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}
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```
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<iframe src="https://ghbtns.com/github-btn.html?user=speechbrain&repo=speechbrain&type=star&count=true&size=large&v=2" frameborder="0" scrolling="0" width="170" height="30" title="GitHub"></iframe>
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<br/><br/>
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# End-to-end SLU model for Timers and Such
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Attention-based RNN sequence-to-sequence model for [Timers and Such](https://arxiv.org/abs/2104.01604) trained on the `train-real` subset. This model checkpoint achieves 86.7% accuracy on `test-real`.
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year = {2021},
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publisher = {GitHub},
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journal = {GitHub repository},
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howpublished = {\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\url{https://github.com/speechbrain/speechbrain}},
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}
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```
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