Tong Li's research while affiliated with The University of Tokyo and other places
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Publications (4)
Most machine translation (MT) research has focused on sentences as translation units (sentence-level MT), and has achieved acceptable translation quality for sentences where cross-sentential context is not required in mainly high-resourced languages. Recently, many researchers have worked on MT models that can consider a cross-sentential context. T...
Sentence-level (SL) machine translation (MT) has reached acceptable quality for many high-resourced languages, but not document-level (DL) MT, which is difficult to 1) train with little amount of DL data; and 2) evaluate, as the main methods and data sets focus on SL evaluation. To address the first issue, we present a document-aligned Japanese-Eng...
While the progress of machine translation of written text has come far in the past several years thanks to the increasing availability of parallel corpora and corpora-based training technologies, automatic translation of spoken text and dialogues remains challenging even for modern systems. In this paper, we aim to boost the machine translation qua...
Citations
... In the Japanese passive statistical machine translation model, the corresponding passive parameters and the parameters to be translated are trained to form the search results with the maximum probability. If different types of passives are decoded, the optimal path for translation is finally formed [12]. ...
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... Parallel dialog corpus There are bilingual dialog corpora, e.g., Business Scene Dialog (Rikters et al., 2019), which includes business negotiation scenes in both Japanese and English. However, our task requires data that include cross-lingual colloquial chats with both appropriate and erroneous translations. ...
