Automatic News Article Generation from Legislative Proceedings: A Phenom-Based Approach

[1]  Toshihiro Kuboi,et al.  predicting the vote using legislative speech , 2018, DG.O.

[2]  Dragomir R. Radev,et al.  LexRank: Graph-based Lexical Centrality as Salience in Text Summarization , 2004, J. Artif. Intell. Res..

[3]  Wai Lam,et al.  Meta-evaluation of Summaries in a Cross-lingual Environment using Content-based Metrics , 2002, COLING.

[4]  Salim Roukos,et al.  Bleu: a Method for Automatic Evaluation of Machine Translation , 2002, ACL.

[5]  Christian Gütl,et al.  Gaining efficiency in human assisted transcription and speech annotation in legislative proceedings , 2018, DG.O.

[6]  Stanley Peters,et al.  Extracting Decisions from Multi-Party Dialogue Using Directed Graphical Models and Semantic Similarity , 2009, SIGDIAL Conference.

[7]  Toshihiro Kuboi,et al.  Learning alignments from legislative discourse , 2018, DG.O.

[8]  Deconstructing Human-assisted Video Transcription and Annotation for Legislative Proceedings , 2020, Digit. Gov. Res. Pract..

[9]  Andreas Stolcke,et al.  Dialogue act modeling for automatic tagging and recognition of conversational speech , 2000, CL.

[10]  Fei Liu,et al.  From Extractive to Abstractive Meeting Summaries: Can It Be Done by Sentence Compression? , 2009, ACL.

[11]  Cuts in Newspaper Staffs Change Meeting Coverage , 2010 .

[12]  Thien Huu Nguyen,et al.  One for All: Neural Joint Modeling of Entities and Events , 2018, AAAI.

[13]  Dilek Z. Hakkani-Tür,et al.  Long story short - Global unsupervised models for keyphrase based meeting summarization , 2010, Speech Commun..