Computer Science ›› 2021, Vol. 48 ›› Issue (1): 247-252.doi: 10.11896/jsjkx.191200088
• Artificial Intelligence • Previous Articles Next Articles
ZHANG Yu-shuai, ZHAO Huan, LI Bo
CLC Number:
[1] HOCHREITER S,SCHMIDHUBER J.Long short-term memory[J].Neural Computation,1997,9(8):1735-1780. [2] DEVLIN J,CHANG M W,LEE K,et al.Bert:Pre-training of deep bidirectional transformers for language understanding[J].arXiv:1810.04805,2018. [3] HOU L X,LI Y L,LI C C.Review of Research on Task-Oriented Spoken Language Understanding[J].Computer Engineering and Applications,2019,55(11):7-15. [4] MCCALLUM A,FREITAG D,PEREIRA F C N.MaximumEntropy Markov Models for Information Extraction and Segmentation[C]//Proceedings of International Conference on Machine Learning.2000:591-598. [5] RAYMOND C,RICCARDI G.Generative and DiscriminativeAlgorithms for Spoken Language Understanding[C]//Procee-dings of Conference of the International Speech Communication Association.2008:1605-1608. [6] MESNIL G,DAUPHIN Y,YAO K,et al.Using Recurrent Neural Networks for Slot Filling in Spoken Language Understanding[J].IEEE/ACM Transactions on Audio,Speech,and Language Processing,2014,23(3):530-539. [7] XU P,SARIKAYA R.Convolutional neural network based triangular CRF for joint intent detection and slot filling[C]//Proceedings of 2013 IEEE Workshop on Automatic Speech Recognition and Understanding.IEEE,2013:78-83. [8] XU Z X,CHE W X,LIU T.Slot filling based on Bi-LSTM-CRF[J].Intelligent Computer and Applications,2017,7(6):91-94. [9] YAO K,PENG B,ZHANG Y,et al.Spoken language under-standing using long short-term memory neural networks[C]//Proceedings of 2014 IEEE Spoken Language Technology Workshop(SLT).IEEE,2014:189-194. [10] PENG B,YAO K.Recurrent Neural Networks with ExternalMemory for Language Understanding[C]//Proceedings of Na-tural Language Processing and Chinese Computing.2015:25-35. [11] VU N T.Sequential Convolutional Neural Networks for SlotFilling in Spoken Language Understanding[C]//Proceedings of 17th Annual Conference of the International Speech Communication Association(ISCA).2016:3250-3254. [12] KURATA G,XIANG B,ZHOU B,et al.Leveraging Sentence-level Information with Encoder LSTM for Natural Language Understanding[J].arXiv:1601.01530,2016. [13] LIU B,LANE I.Multi-Domain Adversarial Learning for Slot Filling in Spoken Language Understanding[J].arXiv:1711.11310,2017. [14] ZHAO L,FENG Z.Improving slot filling in spoken language understanding with joint pointer and attention[C]//Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics(Volume 2:Short Papers).2018:426-431. [15] KIM H Y,ROH Y H,KIM Y G.Data Augmentation by Data Noising for Open-vocabulary Slots in Spoken Language Understanding[C]//Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics:Student Research Workshop.2019:97-102. [16] YOO K M,SHIN Y,LEE S.Data Augmentation for Spoken Language Understanding via Joint Variational Generation[C]//Proceedings of the AAAI Conference on Artificial Intelligence.2019:7402-7409. [17] SHIN Y,YOO K M,LEE S G.Utterance Generation With Varia-tional Auto-Encoder for Slot Filling in Spoken Language Understanding[J].IEEE Signal Processing Letters,2019,26(3):505-509. [18] VASWANI A,SHAZEER N,PARMAR N,et al.Attention isall you need[C]//Proceedings of Advances in Neural Information Processing Systems.2017:5998-6008. [19] PETERS M E,NEUMANN M,IYYER M,et al.Deep contextua-lized word representations[J].arXiv:1802.05365,2018. [20] ZHU Y,KIROS R,ZEMEL R,et al.Aligning books and mo-vies:Towards story-like visual explanations by watching movies and reading books[C]//Proceedings of the IEEE International Conference on Computer Vision.2015:19-27. [21] WU Y,SCHUSTER M,CHEN Z,et al.Google's neural machine translation system:Bridging the gap between human and machine translation[J].arXiv:1609.08144,2016. [22] JIN C,LI W H,JI C,et al.Bi-directional Long Short-term Me-mory Neural Networks for Chinese Word[J].Journal of Chinese Information Processing,2018,32(2):29-37. [23] ZHOU J,XU W.End-to-end learning of semantic role labeling using recurrent neural networks[C]//Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing.2015:1127-1137. |
[1] | WANG Xin-tong, WANG Xuan, SUN Zhi-xin. Network Traffic Anomaly Detection Method Based on Multi-scale Memory Residual Network [J]. Computer Science, 2022, 49(8): 314-322. |
[2] | HOU Yu-tao, ABULIZI Abudukelimu, ABUDUKELIMU Halidanmu. Advances in Chinese Pre-training Models [J]. Computer Science, 2022, 49(7): 148-163. |
[3] | WANG Shan, XU Chu-yi, SHI Chun-xiang, ZHANG Ying. Study on Cloud Classification Method of Satellite Cloud Images Based on CNN-LSTM [J]. Computer Science, 2022, 49(6A): 675-679. |
[4] | HAN Hong-qi, RAN Ya-xin, ZHANG Yun-liang, GUI Jie, GAO Xiong, YI Meng-lin. Study on Cross-media Information Retrieval Based on Common Subspace Classification Learning [J]. Computer Science, 2022, 49(5): 33-42. |
[5] | PAN Zhi-hao, ZENG Bi, LIAO Wen-xiong, WEI Peng-fei, WEN Song. Interactive Attention Graph Convolutional Networks for Aspect-based Sentiment Classification [J]. Computer Science, 2022, 49(3): 294-300. |
[6] | LI Yu-qiang, ZHANG Wei-jiang, HUANG Yu, LI Lin, LIU Ai-hua. Improved Topic Sentiment Model with Word Embedding Based on Gaussian Distribution [J]. Computer Science, 2022, 49(2): 256-264. |
[7] | LIU Kai, ZHANG Hong-jun, CHEN Fei-qiong. Name Entity Recognition for Military Based on Domain Adaptive Embedding [J]. Computer Science, 2022, 49(1): 292-297. |
[8] | LI Zhao-qi, LI Ta. Query-by-Example with Acoustic Word Embeddings Using wav2vec Pretraining [J]. Computer Science, 2022, 49(1): 59-64. |
[9] | TANG Shi-zheng, ZHANG Yan-feng. DragDL:An Easy-to-Use Graphical DL Model Construction System [J]. Computer Science, 2021, 48(8): 220-225. |
[10] | WANG Sheng, ZHANG Yang-sen, CHEN Ruo-yu, XIANG Ga. Text Matching Method Based on Fine-grained Difference Features [J]. Computer Science, 2021, 48(8): 60-65. |
[11] | YU Sheng, LI Bin, SUN Xiao-bing, BO Li-li, ZHOU Cheng. Approach for Knowledge-driven Similar Bug Report Recommendation [J]. Computer Science, 2021, 48(5): 91-98. |
[12] | PENG Bin, LI Zheng, LIU Yong, WU Yong-hao. Automatic Code Comments Generation Method Based on Convolutional Neural Network [J]. Computer Science, 2021, 48(12): 117-124. |
[13] | HUANG Xin, LEI Gang, CAO Yuan-long, LU Ming-ming. Review on Interactive Question Answering Techniques Based on Deep Learning [J]. Computer Science, 2021, 48(12): 286-296. |
[14] | ZHANG Ning, FANG Jing-wen, ZHAO Yu-xuan. Bitcoin Price Forecast Based on Mixed LSTM Model [J]. Computer Science, 2021, 48(11A): 39-45. |
[15] | TIAN Ye, SHOU Li-dan, CHEN Ke, LUO Xin-yuan, CHEN Gang. Natural Language Interface for Databases with Content-based Table Column Embeddings [J]. Computer Science, 2020, 47(9): 60-66. |
|