Jing Su


pdf bib
Generating Description for Sequential Images with Local-Object Attention Conditioned on Global Semantic Context
Jing Su | Chenghua Lin | Mian Zhou | Qingyun Dai | Haoyu Lv
Proceedings of the Workshop on Intelligent Interactive Systems and Language Generation (2IS&NLG)


pdf bib
Topic Stability over Noisy Sources
Jing Su | Derek Greene | Oisín Boydell
Proceedings of the 2nd Workshop on Noisy User-generated Text (WNUT)

Topic modelling techniques such as LDA have recently been applied to speech transcripts and OCR output. These corpora may contain noisy or erroneous texts which may undermine topic stability. Therefore, it is important to know how well a topic modelling algorithm will perform when applied to noisy data. In this paper we show that different types of textual noise can have diverse effects on the stability of topic models. On the other hand, topic model stability is not consistent with the same type but different levels of noise. We introduce a dictionary filtering approach to address this challenge, with the result that a topic model with the correct number of topics is always identified across different levels of noise.


pdf bib
Assessing the effectiveness of conversational features for dialogue segmentation in medical team meetings and in the AMI corpus
Saturnino Luz | Jing Su
Proceedings of the SIGDIAL 2010 Conference