Segmenting Subtitles for Correcting ASR Segmentation Errors

Autor: Zhengping Jiang, Chris Kedzie, Peter Bell, Elena Zotkina, Faisal Ladhak, Elsbeth Turcan, David Wan, Kathleen R. McKeown, Petra Galuščáková

Publikováno v: EACL
Wan, D, Kedzie, C, Ladhak, F, Turcan, E, Galuščáková, P, Zotkina, E, Jiang, Z, Bell, P & McKeown, K 2021, Segmenting Subtitles for Correcting ASR Segmentation Errors . in Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume . pp. 2842-2854, 16th conference of the European Chapter of the Association for Computational Linguistics, Virtual Conference, 19/04/21 . < https://www.aclweb.org/anthology/2021.eacl-main.248 >

Typical ASR systems segment the input audio in toutterances using purely acoustic information, which may not resemble the sentence-like units that are expected by conventional machine translation (MT) systems for Spoken Language Translation. In this

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::00eb937b786fb933b25f1023c604eb1d
http://arxiv.org/abs/2104.07868

The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics

Autor: Thibault Sellam, Vikas Raunak, Cristina Garbacea, Simon Mille, Tatsunori Hashimoto, Miruna-Adriana Clinciu, Ankur P. Parikh, Angelina McMillan-Major, Samira Shaikh, Kaustubh Dhole, Pawan Sasanka Ammanamanchi, Anuoluwapo Aremu, Laura Perez-Beltrachini, Marco Antonio Sobrevilla Cabezudo, Juan Diego Rodriguez, Sashank Santhanam, Bodhisattwa Prasad Majumder, Dhruv Kumar, Esin Durmus, Dipanjan Das, Wei Xu, Wanyu Du, Vitaly Nikolaev, Faisal Ladhak, Moin Nadeem, Chris Chinenye Emezue, Varun Gangal, Diyi Yang, Yangfeng Ji, João Sedoc, Aman Madaan, Shailza Jolly, Saad Mahamood, Karmanya Aggarwal, Emiel van Miltenburg, Antoine Bosselut, Salomey Osei, Jiawei Zhou, Yufang Hou, Harsh Jhamtani, Niranjan Ramesh Rao, Anastasia Shimorina, Shashi Narayan, Akhila Yerukola, Nishant Subramani, Sebastian Gehrmann, Hendrik Strobelt, Khyathi Raghavi Chandu, Yacine Jernite, Tosin P. Adewumi, Mihir Kale, Khyati Mahajan, Andre Niyongabo Rubungo, Pedro Henrique Martins, Ondřej Dušek, Mounica Maddela

Publikováno v: Proceedings of the 1st Workshop on Natural Language Generation, Evaluation, and Metrics (GEM 2021)
Proceedings of the 1st Workshop on Natural Language Generation, Evaluation, and Metrics (GEM 2021), Aug 2021, Online, France. pp.96-120, ⟨10.18653/v1/2021.gem-1.10⟩
Tilburg University-PURE
Proceedings of the 1st Workshop on Natural Language Generation, Evaluation, and Metrics (GEM 2021), 96-120
STARTPAGE=96;ENDPAGE=120;TITLE=Proceedings of the 1st Workshop on Natural Language Generation, Evaluation, and Metrics (GEM 2021)

International audience; We introduce GEM, a living benchmark for natural language Generation (NLG), its Evaluation, and Metrics. Measuring progress in NLG relies on a constantly evolving ecosystem of automated metrics, datasets, and human evaluation

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::56549f809a95ad121bc57aac47f790d8
https://doi.org/10.18653/v1/2021.gem-1.10

The Role of Pragmatic and Discourse Context in Determining Argument Impact

Autor: Claire Cardie, Faisal Ladhak, Esin Durmus

Publikováno v: EMNLP/IJCNLP (1)

Research in the social sciences and psychology has shown that the persuasiveness of an argument depends not only the language employed, but also on attributes of the source/communicator, the audience, and the appropriateness and strength of the argum

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a7c650a98d8e348a04227651df2b9510
http://arxiv.org/abs/2004.03034

Determining Relative Argument Specificity and Stance for Complex Argumentative Structures

Autor: Faisal Ladhak, Esin Durmus, Claire Cardie

Publikováno v: ACL (1)

Systems for automatic argument generation and debate require the ability to (1) determine the stance of any claims employed in the argument and (2) assess the specificity of each claim relative to the argument context. Existing work on understanding

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cc6f78eb1408b5f9f2a89ea076dad123
https://doi.org/10.18653/v1/p19-1456

LatticeRnn: Recurrent Neural Networks Over Lattices

Autor: Faisal Ladhak, Lambert Mathias, Bjorn Hoffmeister, Ankur Gandhe, Ariya Rastrow, Markus Dreyer

Publikováno v: INTERSPEECH

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::25a7c9889f80b58a3de46abfe1d470c5
https://doi.org/10.21437/interspeech.2016-1583