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The ARIEL-CMU Systems for LoReHLT18

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arxiv 1902.08899 v1 pith:7TFEUZTH submitted 2019-02-24 cs.CL

Aditi Chaudhary , Siddharth Dalmia , Junjie Hu , Xinjian Li , Austin Matthews , Aldrian Obaja Muis , Naoki Otani , Shruti Rijhwani
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Zaid Sheikh Nidhi Vyas Xinyi Wang Jiateng Xie Ruochen Xu Chunting Zhou Peter J. Jansen Yiming Yang Lori Levin Florian Metze Teruko Mitamura David R. Mortensen Graham Neubig Eduard Hovy Alan W Black Jaime Carbonell Graham V. Horwood Shabnam Tafreshi Mona Diab Efsun S. Kayi Noura Farra Kathleen McKeown
This is my paper · ORCID
classification cs.CL
keywords ariel-cmuspeechtextdescribesdetectiondiscoveryentityevaluations
verification ladder T0 review T1 audit T2 compute T3 formal

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This paper describes the ARIEL-CMU submissions to the Low Resource Human Language Technologies (LoReHLT) 2018 evaluations for the tasks Machine Translation (MT), Entity Discovery and Linking (EDL), and detection of Situation Frames in Text and Speech (SF Text and Speech).

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  1. SANTLR: Speech Annotation Toolkit for Low Resource Languages

    cs.CL 2019-08 reject novelty 4.0 of 10

    SANTLR is a new web-based speech annotation toolkit for low-resource languages that ranks utterances by ease and usefulness, but its claimed benefit is unvalidated.

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