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- W2951878118 abstract "We experiment graph-based Semi-Supervised Learning (SSL) of Conditional Random Fields (CRF) for the application of Spoken Language Understanding (SLU) on unaligned data. The aligned labels for examples are obtained using IBM Model. We adapt a baseline semi-supervised CRF by defining new feature set and altering the label propagation algorithm. Our results demonstrate that our proposed approach significantly improves the performance of the supervised model by utilizing the knowledge gained from the graph." @default.
- W2951878118 created "2019-06-27" @default.
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- W2951878118 date "2017-01-30" @default.
- W2951878118 modified "2023-09-27" @default.
- W2951878118 title "Graph-Based Semi-Supervised Conditional Random Fields For Spoken Language Understanding Using Unaligned Data" @default.
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