Benjamin Cowan


2022

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An Empirical Study of Topic Transition in Dialogue
Mayank Soni | Brendan Spillane | Leo Muckley | Orla Cooney | Emer Gilmartin | Christian Saam | Benjamin Cowan | Vincent Wade
Proceedings of the 3rd Workshop on Computational Approaches to Discourse

Although topic transition has been studied in dialogue for decades, only a handful of corpora based quantitative studies have been conducted to investigate the nature of topic transitions. Towards this end, this study annotates 215 conversations from the switchboard corpus, perform quantitative analysis and finds that 1) longer conversations consists of more topic transitions, 2) topic transition are usually lead by one participant and 3) we found no pattern in time series progression of topic transition. We also model topic transition with a precision of 91%.

2020

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MT syntactic priming effects on L2 English speakers
Natália Resende | Benjamin Cowan | Andy Way
Proceedings of the 22nd Annual Conference of the European Association for Machine Translation

In this paper, we tested 20 Brazilian Portuguese speakers at intermediate and advanced English proficiency levels to investigate the influence of Google Translate’s MT system on the mental processing of English as a second language. To this end, we employed a syntactic priming experimental paradigm using a pretest-priming design which allowed us to compare participants’ linguistic behaviour before and after a translation task using Google Translate. Results show that, after performing a translation task with Google Translate, participants more frequently described images in English using the syntactic alternative previously seen in the output of Google Translate, compared to the translation task with no prior influence of the MT output. Results also show that this syntactic priming effect is modulated by English proficiency levels.