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pro vyhledávání: '"Scholman, Merel"'
Non-verbal communication often comprises of semantically rich gestures that help convey the meaning of an utterance. Producing such semantic co-speech gestures has been a major challenge for the existing neural systems that can generate rhythmic beat
Externí odkaz:
http://arxiv.org/abs/2412.06786
Nigerian Pidgin is an English-derived contact language and is traditionally an oral language, spoken by approximately 100 million people. No orthographic standard has yet been adopted, and thus the few available Pidgin datasets that exist are charact
Externí odkaz:
http://arxiv.org/abs/2404.18264
Pre-trained large language models, such as ChatGPT, archive outstanding performance in various reasoning tasks without supervised training and were found to have outperformed crowdsourcing workers. Nonetheless, ChatGPT's performance in the task of im
Externí odkaz:
http://arxiv.org/abs/2402.04918
Developing effective spoken language processing systems for low-resource languages poses several challenges due to the lack of parallel data and limited resources for fine-tuning models. In this work, we target on improving upon both text classificat
Externí odkaz:
http://arxiv.org/abs/2307.00382
Autor:
Pyatkin, Valentina, Yung, Frances, Scholman, Merel C. J., Tsarfaty, Reut, Dagan, Ido, Demberg, Vera
Disagreement in natural language annotation has mostly been studied from a perspective of biases introduced by the annotators and the annotation frameworks. Here, we propose to analyze another source of bias: task design bias, which has a particularl
Externí odkaz:
http://arxiv.org/abs/2304.00815
Discourse-annotated corpora are an important resource for the community, but they are often annotated according to different frameworks. This makes comparison of the annotations difficult, thereby also preventing researchers from searching the corpor
Externí odkaz:
http://arxiv.org/abs/1704.08893
Publikováno v:
Discourse Processes; Sep2024, Vol. 61 Issue 8, p381-403, 23p
Publikováno v:
Journal of Experimental Psychology. Learning, Memory & Cognition. May2024, Vol. 50 Issue 5, p796-807. 12p.
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Publikováno v:
In Journal of Memory and Language December 2017 97:47-60