Report
Graph-Based Semi-Supervised Conditional Random Fields For Spoken Language Understanding Using Unaligned Data
| العنوان: | Graph-Based Semi-Supervised Conditional Random Fields For Spoken Language Understanding Using Unaligned Data |
|---|---|
| المؤلفون: | Aliannejadi, Mohammad, Kiaeeha, Masoud, Khadivi, Shahram, Ghidary, Saeed Shiry |
| سنة النشر: | 2017 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computation and Language |
| الوصف: | 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. Comment: Workshop of The Australasian Language Technology Association |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/1701.08533 |
| رقم الانضمام: | edsarx.1701.08533 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |