Renlong Ai


2018

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TQ-AutoTest – An Automated Test Suite for (Machine) Translation Quality
Vivien Macketanz | Renlong Ai | Aljoscha Burchardt | Hans Uszkoreit
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)

2017

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Streaming Text Analytics for Real-Time Event Recognition
Philippe Thomas | Johannes Kirschnick | Leonhard Hennig | Renlong Ai | Sven Schmeier | Holmer Hemsen | Feiyu Xu | Hans Uszkoreit
Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017

A huge body of continuously growing written knowledge is available on the web in the form of social media posts, RSS feeds, and news articles. Real-time information extraction from such high velocity, high volume text streams requires scalable, distributed natural language processing pipelines. We introduce such a system for fine-grained event recognition within the big data framework Flink, and demonstrate its capabilities for extracting and geo-locating mobility- and industry-related events from heterogeneous text sources. Performance analyses conducted on several large datasets show that our system achieves high throughput and maintains low latency, which is crucial when events need to be detected and acted upon in real-time. We also present promising experimental results for the event extraction component of our system, which recognizes a novel set of event types. The demo system is available at http://dfki.de/sd4m-sta-demo/.

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Common Round: Application of Language Technologies to Large-Scale Web Debates
Hans Uszkoreit | Aleksandra Gabryszak | Leonhard Hennig | Jörg Steffen | Renlong Ai | Stephan Busemann | Jon Dehdari | Josef van Genabith | Georg Heigold | Nils Rethmeier | Raphael Rubino | Sven Schmeier | Philippe Thomas | He Wang | Feiyu Xu
Proceedings of the Software Demonstrations of the 15th Conference of the European Chapter of the Association for Computational Linguistics

Web debates play an important role in enabling broad participation of constituencies in social, political and economic decision-taking. However, it is challenging to organize, structure, and navigate a vast number of diverse argumentations and comments collected from many participants over a long time period. In this paper we demonstrate Common Round, a next generation platform for large-scale web debates, which provides functions for eliciting the semantic content and structures from the contributions of participants. In particular, Common Round applies language technologies for the extraction of semantic essence from textual input, aggregation of the formulated opinions and arguments. The platform also provides a cross-lingual access to debates using machine translation.

2016

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Real-Time Discovery and Geospatial Visualization of Mobility and Industry Events from Large-Scale, Heterogeneous Data Streams
Leonhard Hennig | Philippe Thomas | Renlong Ai | Johannes Kirschnick | He Wang | Jakob Pannier | Nora Zimmermann | Sven Schmeier | Feiyu Xu | Jan Ostwald | Hans Uszkoreit
Proceedings of ACL-2016 System Demonstrations

2015

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A System Demonstration of a Framework for Computer Assisted Pronunciation Training
Renlong Ai | Feiyu Xu
Proceedings of ACL-IJCNLP 2015 System Demonstrations

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Semi-automatic Generation of Multiple-Choice Tests from Mentions of Semantic Relations
Renlong Ai | Sebastian Krause | Walter Kasper | Feiyu Xu | Hans Uszkoreit
Proceedings of the 2nd Workshop on Natural Language Processing Techniques for Educational Applications

2014

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Sprinter: Language Technologies for Interactive and Multimedia Language Learning
Renlong Ai | Marcela Charfuelan | Walter Kasper | Tina Klüwer | Hans Uszkoreit | Feiyu Xu | Sandra Gasber | Philip Gienandt
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

Modern language learning courses are no longer exclusively based on books or face-to-face lectures. More and more lessons make use of multimedia and personalized learning methods. Many of these are based on e-learning solutions. Learning via the Internet provides 7/24 services that require sizeable human resources. Therefore we witness a growing economic pressure to employ computer-assisted methods for improving language learning in quality, efficiency and scalability. In this paper, we will address three applications of language technologies for language learning: 1) Methods and strategies for pronunciation training in second language learning, e.g., multimodal feedback via visualization of sound features, speech verification and prosody transplantation; 2) Dialogue-based language learning games; 3) Application of parsing and generation technologies to the automatic generation of paraphrases for the semi-automatic production of learning material.

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MAT: a tool for L2 pronunciation errors annotation
Renlong Ai | Marcela Charfuelan
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

In the area of Computer Assisted Language Learning(CALL), second language (L2) learners’ spoken data is an important resource for analysing and annotating typical L2 pronunciation errors. The annotation of L2 pronunciation errors in spoken data is not an easy task though, normally it requires manual annotation from trained linguists or phoneticians. In order to facilitate this task, in this paper, we present the MAT tool, a web-based tool intended to facilitate the annotation of L2 learners’ pronunciation errors at various levels. The tool has been designed taking into account recent studies on error detection in pronunciation training. It also aims at providing an easy and fast annotation process via a comprehensive and friendly user interface. The tool is based on the MARY TTS open source platform, from which it uses the components: text analyser (tokeniser, syllabifier, phonemiser), phonetic aligner and speech signal processor. Annotation results at sentence, word, syllable and phoneme levels are stored in XML format. The tool is currently under evaluation with a L2 learners’ spoken corpus recorded in the SPRINTER (Language Technology for Interactive, Multi-Media Online Language Learning) project.

2013

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Perceptual Feedback in Computer Assisted Pronunciation Training: A Survey
Renlong Ai
Proceedings of the Student Research Workshop associated with RANLP 2013