|
|
| 第1行： |
第1行： |
| − | =Publication rules=
| + | [[delivery-2016|2016]] |
| − | [[ASR-publication process|CSLT Publication Rules]] | + | |
| − | | + | |
| − | | + | |
| − | =Technical report=
| + | |
| − | | + | |
| − | #[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/1/15/Sda.pdf TRP-20160013: Sparse Discriminative Analysis and Its Application in Distraction Classification, Dong Wang]
| + | |
| − | #[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/9/95/Dkeyword.pdf TRP-20160010: Highly Restricted Keyword Selection Based on Sparse Analysis for Uyghur Text Categorization, Dong Wang, Askar Humdulla, Rayilam Parhat, Javier Tejedor]
| + | |
| − | #[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/2/2b/RNNG_Code_Use_Guide_simplified.pdf TRP-20160009: RNNG Code User Guide, Shiyue Zhang and Yang Feng]
| + | |
| − | #[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/c/c4/Memory-atten-model-public.pdf TRP-20160008: Different styles of poetry generation based on memory model, Jiyuan Zhang,Yang Feng and Dong Wang]
| + | |
| − | #[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/7/76/Distraction.pdf TRP-20160007: Distraction Detection Using Sparse Discriminative Analysis, Dong Wang and Guozhen Zhao]
| + | |
| − | #[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/6/6a/Visual.pdf TRP-20160006: Visualization Analysis for Recurrent Networks, Zhiyuan Tang, Ying Shi and Dong Wang]
| + | |
| − | #[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/9/90/Distributed_Representation_Learning_for_Knowledge_Graphs_with_Entity_Descriptions.pdf TRP-20160005: Distributed Representation Learning for Knowledge Graphs with Entity Descriptions; Miao Fan, Qiang Zhou, Thomas Fang Zheng, Ralph Grishman]
| + | |
| − | #[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/7/7d/Cslt-trp-template.pdf TRP-20160004: A Review of Neural QA, Tianyi Luo and Dong Wang]
| + | |
| − | #[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/8/88/Trp20160003.pdf TRP-20160003: A study of Similar Word Model for Unfrequent Word Enhancement in Speech Recognition, Xi Ma, Dong Wang and Javier Tejedor]
| + | |
| − | #[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/3/39/How_to_deal_with_low_frequency_words.pdf TRP-20160002: Low-Frequency Words Embedding, Chao Xing, Yiqiao Pan, Dong Wang]
| + | |
| − | #[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/b/b6/Max-margin.pdf TRP-20160001: Max-margin metric learning for speaker recognition, Lantian Li, Chao Xing, Dong Wang]
| + | |
| − | | + | |
| − | =Patent=
| + | |
| − | | + | |
| − | #王东 邢超 张之勇 赵梦原 一种面向混合语言的语音合成方法 [FreeNeb] [[媒体文件:一种中英文混合的语音合成方法.docx|交底书]]
| + | |
| − | #王东 张之勇 赵梦原 黄伟明 李国强，一种日语语音识别系统训练方法 [同方] [[媒体文件:一种日语语音识别系统训练方法.docx|交底书]]
| + | |
| − | #汪洋，王东，刘荣 在线强化学习交易策略 [张露] [[媒体文件:在线强化学习交易策略.docx|文底书]]
| + | |
| − | #王东，白紫薇，冯洋，杜新凯，游士学，基于LSTM模型的现代文到古诗的转换技术 [汇联] [[媒体文件:基于LSTM模型的现代文到古诗的转换技术.docx|交底书]]
| + | |
| − | #王东，张记袁，冯洋，杜新凯，游士学， 一种基于共同语义空间的个性化音乐生成技术 [汇联] [[媒体文件:一种基于共同语义空间的个性化音乐生成技术.docx|交底书]]
| + | |
| − | | + | |
| − | =Database=
| + | |
| − | | + | |
| − | {| class="wikitable"
| + | |
| − | ! name !! type!! size !! dir !! description
| + | |
| − | |-
| + | |
| − | |lyric||text||-||corpora/art/lyric|| song lyric data collected by Jiyuan Zhang
| + | |
| − | |-
| + | |
| − | |poem||text||-||corpora/art/poem|| Traditional Chinese poem data collected by Qixin Wang and Jiyuan Zhang
| + | |
| − | |-
| + | |
| − | |cnsong||text||-||corpora/art/song|| Chinese Song sentences collected by Aiting Liu
| + | |
| − | |-
| + | |
| − | |factordb||transaction||-||corpora/finance/factordb|| Factor database collected by Wangyang
| + | |
| − | |}
| + | |
| − | | + | |
| − | =Code=
| + | |
| − | | + | |
| − | {| class="wikitable"
| + | |
| − | ! Code Name!! Author !! Description
| + | |
| − | |-
| + | |
| − | |viewExp||Wang Yang|| The experiment platform of the Finance team [http://git.cslt.org/finance/viewexp/tree/master link]
| + | |
| − | |-
| + | |
| − | |vvBeam||Wang Dong|| Beamforming using superdirective array [http://git.cslt.org/speech/beam link]
| + | |
| − | |-
| + | |
| − | |}
| + | |
| − | =Model and System=
| + | |
