Automatic generation of large-scale paraphrases

Research on paraphrase has mostly focussed on lexical or syntactic variation within individual sentences. Our concern is with larger-scale paraphrases, from multiple sentences or paragraphs to entire documents. In this paper we address the problem of generating paraphrases of large chunks of texts. We ground our discussion through a worked example of extending an existing NLG system to accept as input a source text, and to generate a range of fluent semantically-equivalent alternatives, varying not only at the lexical and syntactic levels, but also in document structure and layout

Semantically Conditioned LSTM-based Natural Language Generation for Spoken Dialogue Systems

Natural language generation (NLG) is a critical component of spoken dialogue and it has a significant impact both on usability and perceived quality. Most NLG systems in common use employ rules and heuristics and tend to generate rigid and stylised responses without the natural variation of human language. They are also not easily scaled to systems covering multiple domains and languages. This paper presents a statistical language generator based on a semantically controlled Long Short-term Memory (LSTM) structure. The LSTM generator can learn from unaligned data by jointly optimising sentence planning and surface realisation using a simple cross entropy training criterion, and language variation can be easily achieved by sampling from output candidates. With fewer heuristics, an objective evaluation in two differing test domains showed the proposed method improved performance compared to previous methods. Human judges scored the LSTM system higher on informativeness and naturalness and overall preferred it to the other systems.Comment: To be appear in EMNLP 201

Un corrector gramatical basat en cerques per Internet

En aquest article presentem un corrector gramatical de l'anglès destinat a escriptors no angloparlants. La principal característica d'aquest corrector és l'ús d'un motor de cerca per Internet. Com que hi ha un gran nombre de pàgines web escrites en anglès, el sistema fa la hipòtesi que un segment de text que no és present en cap pàgina web és probablement un segment de text mal escrit. El sistema també fa la hipòtesi que a la Xarxa hi trobarà exemples que ensenyaran a l'usuari com ha d'expressar el contingut del segment de text d'una manera gramatical i idiomàtica. Per tant, un cop el corrector avisa l'usuari que és millor verificar un segment del seu text, el motor cerca contextos que poden ser útils a la persona que escriu a l'hora de decidir si corregeix el segment o no. Gràcies també a l'ús d'un motor de cerca, el corrector suggereix a l'escriptor que utilitzi expressions que són més freqüents a la Xarxa en comptes de l'expressió que ha escrit

Fra Laboratoriet for Opvarmnning og Ventilation til Internationalt Center for Indeklima og Energi

En historisk oversigt i anledning af 125-året for en selvstændig lærestol i Opvarmning og Ventilation og 75-året for oprettelsen af Laboratoriet for Opvarmning og Ventilatio

Intrinsic vs. extrinsic evaluation measures for referring expression generation

In this paper we present research in which we apply (i) the kind of intrinsic evaluation metrics that are characteristic of current comparative HLT evaluation, and (ii) extrinsic, human task-performance evaluations more in keeping with NLG traditions, to 15 systems implementing a language generation task. We analyse the evaluation results and find that there are no significant correlations between intrinsic and extrinsic evaluation measures for this task.peer-reviewe

Statistical Function Tagging and Grammatical Relations of Myanmar Sentences

This paper describes a context free grammar (CFG) based grammatical relations for Myanmar sentences which combine corpus-based function tagging system. Part of the challenge of statistical function tagging for Myanmar sentences comes from the fact that Myanmar has free-phrase-order and a complex morphological system. Function tagging is a pre-processing step to show grammatical relations of Myanmar sentences. In the task of function tagging, which tags the function of Myanmar sentences with correct segmentation, POS (part-of-speech) tagging and chunking information, we use Naive Bayesian theory to disambiguate the possible function tags of a word. We apply context free grammar (CFG) to find out the grammatical relations of the function tags. We also create a functional annotated tagged corpus for Myanmar and propose the grammar rules for Myanmar sentences. Experiments show that our analysis achieves a good result with simple sentences and complex sentences.Comment: 16 pages, 7 figures, 8 tables, AIAA-2011 (India). arXiv admin note: text overlap with arXiv:0912.1820 by other author

Lexical Parameters, Based on Corpus Analysis of English and Swedish Cancer Data, of Relevance for NLG

Proceedings of the 16th Nordic Conference of Computational Linguistics NODALIDA-2007. Editors: Joakim Nivre, Heiki-Jaan Kaalep, Kadri Muischnek and Mare Koit. University of Tartu, Tartu, 2007. ISBN 978-9985-4-0513-0 (online) ISBN 978-9985-4-0514-7 (CD-ROM) pp. 333-336