Antoine Tixier


2020

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Speaker-change Aware CRF for Dialogue Act Classification
Guokan Shang | Antoine Tixier | Michalis Vazirgiannis | Jean-Pierre Lorré
Proceedings of the 28th International Conference on Computational Linguistics

Recent work in Dialogue Act (DA) classification approaches the task as a sequence labeling problem, using neural network models coupled with a Conditional Random Field (CRF) as the last layer. CRF models the conditional probability of the target DA label sequence given the input utterance sequence. However, the task involves another important input sequence, that of speakers, which is ignored by previous work. To address this limitation, this paper proposes a simple modification of the CRF layer that takes speaker-change into account. Experiments on the SwDA corpus show that our modified CRF layer outperforms the original one, with very wide margins for some DA labels. Further, visualizations demonstrate that our CRF layer can learn meaningful, sophisticated transition patterns between DA label pairs conditioned on speaker-change in an end-to-end way. Code is publicly available.

2018

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Unsupervised Abstractive Meeting Summarization with Multi-Sentence Compression and Budgeted Submodular Maximization
Guokan Shang | Wensi Ding | Zekun Zhang | Antoine Tixier | Polykarpos Meladianos | Michalis Vazirgiannis | Jean-Pierre Lorré
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

We introduce a novel graph-based framework for abstractive meeting speech summarization that is fully unsupervised and does not rely on any annotations. Our work combines the strengths of multiple recent approaches while addressing their weaknesses. Moreover, we leverage recent advances in word embeddings and graph degeneracy applied to NLP to take exterior semantic knowledge into account, and to design custom diversity and informativeness measures. Experiments on the AMI and ICSI corpus show that our system improves on the state-of-the-art. Code and data are publicly available, and our system can be interactively tested.

2017

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Real-Time Keyword Extraction from Conversations
Polykarpos Meladianos | Antoine Tixier | Ioannis Nikolentzos | Michalis Vazirgiannis
Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers

We introduce a novel method to extract keywords from meeting speech in real-time. Our approach builds on the graph-of-words representation of text and leverages the k-core decomposition algorithm and properties of submodular functions. We outperform multiple baselines in a real-time scenario emulated from the AMI and ICSI meeting corpora. Evaluation is conducted against both extractive and abstractive gold standard using two standard performance metrics and a newer one based on word embeddings.

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Combining Graph Degeneracy and Submodularity for Unsupervised Extractive Summarization
Antoine Tixier | Polykarpos Meladianos | Michalis Vazirgiannis
Proceedings of the Workshop on New Frontiers in Summarization

We present a fully unsupervised, extractive text summarization system that leverages a submodularity framework introduced by past research. The framework allows summaries to be generated in a greedy way while preserving near-optimal performance guarantees. Our main contribution is the novel coverage reward term of the objective function optimized by the greedy algorithm. This component builds on the graph-of-words representation of text and the k-core decomposition algorithm to assign meaningful scores to words. We evaluate our approach on the AMI and ICSI meeting speech corpora, and on the DUC2001 news corpus. We reach state-of-the-art performance on all datasets. Results indicate that our method is particularly well-suited to the meeting domain.

2016

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A Graph Degeneracy-based Approach to Keyword Extraction
Antoine Tixier | Fragkiskos Malliaros | Michalis Vazirgiannis
Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing

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GoWvis: A Web Application for Graph-of-Words-based Text Visualization and Summarization
Antoine Tixier | Konstantinos Skianis | Michalis Vazirgiannis
Proceedings of ACL-2016 System Demonstrations