Name
Abstract | ||
|---|---|---|
Many problems in natural language processing (NLP) can be cast as the problem of segmenting a sequence. In this article, we combine the semi-Markov conditional random fields (semi-CRF) with neural networks to solve NLP segmentation problems. We focus on the segment representation in neural semi-CRF which is important to the performance. Based on our preliminary work in Liu et al.[1], we represent ... |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/TASLP.2020.2964960 | IEEE/ACM Transactions on Audio, Speech, and Language Processing |
Keywords | DocType | Volume |
Encoding,Neural networks,Feature extraction,Natural language processing,Syntactics,Bit error rate,Speech processing | Journal | 28 |
ISSN | Citations | PageRank |
2329-9290 | 1 | 0.35 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yijia Liu | 1 | 49 | 7.34 |
| Wanxiang Che | 2 | 711 | 66.39 |
| Bing Qin | 3 | 1076 | 72.82 |
| Ting Liu | 4 | 2735 | 232.31 |