Weekly meeting
来自cslt Wiki
| Date | Speaker | Title | Materials | On duty |
|---|---|---|---|---|
| 2012/08/27 | Dong Wang | Heterogeneous Convolutive Non-negative Sparse Coding | slides paper | |
| 2012/09/03 | NO Meeting | |||
| 2012/09/10 | NO Meeting | |||
| 2012/09/17 | WALEED ABDULLA | Auditory Based Feature Vectors for Speech Recognition | slides | 范淼 |
| 2012/09/24 | 刘超 | N-gram FST indexing for Spoken Term Detection | slides | 尹聪 |
| 范淼 | Micro-blogging, Wikipedia, Folksonomy, What's Next? | slides | ||
| 2012/10/08 | NO Meeting | |||
| 2012/10/15 | NO Meeting | |||
| 2012/10/22 | Wu Xiaojun | speaker recognition in CSLT | slides | 卡尔 |
| 2012/10/29 | 王军 | An overview of Automatic Speaker Diarization Systems | slides | 别凡虎 |
| 2012/11/05 | 别凡虎 | Experiments on Emotional Speaker Recognition | slides | 刘超 |
| 2012/11/12 | 唐国瑜 | Statistical Word Sense Improves Document Clustering | slides | 邱晗 |
| 2012/11/19 | 张陈昊 | TDSR with Long-term Features Based on Functional Data Analysis | slides | 王俊俊 |
| 2012/11/26 | 王琳琳 | Time-Varying Speaker Recognition: An Introduction | slides | 龚宬 |
| 2012/12/03 | No meeting | |||
| 2012/12/10 | No meeting | |||
| 2012/12/17 | No meeting | |||
| 2012/01/07 | ||||
| 2012/01/07 | 王军 | 基于DF-MAP的说话人模型训练方法 | slides | 唐国瑜 |
| 2012/01/14 | 王东 | Computing in CSLT | slides | 王琳琳 |
| 2013/03/04 | 王军 | Sequential Adaptive Learning for Speaker Verification | slides | 别凡虎 |
| 2013/03/11 | Du Jinle | VAD stuff | ||
| 2013/03/18 | ||||
| 2013/03/25 | ||||
| 2013/04/01 | ||||
| 2013/04/08 | 张陈昊 | A Fishervoice based Feature Fusion Method for SUSR | slides | 谢仲达 |
| 2013/04/15 | 龚宬 | An Exploration on Influence Factors of VAD's Performance in Speaker Recognition | slides | |
| 2013/04/22 | 王俊俊 | Understanding the Query: THCIB and THUIS at NTCIR-10 Intent Task | slides | |
| 2013/04/29 | ||||
| 2013/05/06 | 别凡虎 | MLLR on Emotional Speaker Recognition | slides | |
| 2013/05/13 | 刘超 | The Use of Deep Neural Network for Speech Recognition | slides | |
| 2013/05/20 | ||||
| 2013/05/27 | 王琳琳 | 说话人识别中的时变鲁棒性问题研究 | slides | |
| 2013/06/03 | 王俊俊 | 汉语搜索结果聚类系统研究与实现 | slides | |
| 2013/06/10 | ||||
| 2013/06/17 | 范淼 | Relation Extraction | slides | |
| 2013/06/24 | 唐国瑜 | Incorporating Statistical Word Senses in Topic Model | slides | |
| 2013/07/01 | ||||
| 2013/07/08 | ||||
| 2013/07/15 | ||||
| 2013/09/09 | 王东 | Research Frontier in Speech Technology | slides | |
| 2013/09/16 | ||||
| 2013/09/23 | ||||
| 2013/09/30 | ||||
| 2013/10/07 | ||||
| 2013/10/14 | ||||
| 2013/10/21 | 范淼 | Transduction Classification with Matrix Completion （中文报告） | slides paper | 李蓝天 |
| 2013/10/28 | ||||
| 2013/11/04 | 王军 | 基于i-vector的intersession补偿及打分方法(综述) | slides | |
| 2013/11/11 | 张陈昊 | PLDA介绍及PLDA在说话人识别中的应用 | slides | 唐国瑜 |
| 2013/11/18 | 别凡虎 | i-vector理论介绍（讨论） | slides | 王军 |
| 2013/11/25 | 刘超 | Pruning Neural Networks By Optimal Brain Damage(综述) | slides | 范淼 |
| 2013/12/02 | 范淼 | Distant Supervision for Relation Extraction with Matrix Completion （英文报告） | slides | 李蓝天 |
| 2013/12/09 | Dong Wang | Introduction to the HMM-based speech synthesis | slides | |
| 2013/12/16 | 张陈昊 | 语音研究中的基元介绍 | slides | |
| 2013/12/23 | Dong Wang | Introduction to the HMM-based speech synthesis (2) | slides | |
| 2013/12/23 | ||||
| 2013/12/30 | 刘荣 | continuous space language model | slides | 刘超 |
| 2014/01/06 | ||||
| 2014/01/13 | ||||
| 2014/01/20 | ||||
| 2014/02/24 | ||||
| 2014/03/03 | ||||
| 2014/03/10 | 范淼 | Distant Supervision for Information Extraction (英文报告) | 李蓝天 | |
| 2014/03/17 | 唐国瑜 | Topic Models Incorporating Statistical Word Senses | slides | |
| 2014/03/24 | 孟祥涛 | Noisy training for Deep Neural Networks | ||
| 2014/03/31 | 范淼 | Translating Embeddings for Modeling Multi-relational Data （中文报告） | paper | 李蓝天 |
| 2014/04/07 | ||||
| 2014/04/14 | Wang Jun | I-vector and PLDA in depth | slides | |
| 2014/04/21 | 邱晗 | 汉语事件句式规范化处理 | slides | |
| 2014/04/28 | 唐国瑜 | Some papers in CICLing2014 | slides | 刘超 |
| 2014/05/05 | ||||
| 2014/05/12 | 卡尔 | paper introduction | slides | 邱晗 |
| 2014/05/19 | 邱晗 | 硕士论文工作介绍 | 卡尔 | |
| Liu Chao | master proposal: sparse and deep neural networks |
