Images as Context in Statistical Machine Translation∗
نویسندگان
چکیده
This paper reports ongoing experiments towards exploiting the use of images to provide additional context for statistical machine translation (SMT). We investigate whether this contextual information can be helpful in targeting two well-known challenges in machine translation: ambiguity (incorrect translation of words that have multiple senses) and out-of-vocabulary words (words left untranslated). As a motivating example, consider Figure 1, which depicts a news headline extracted from the BBC News website and its incorrect translation into Portuguese, as generated by the Google Translate online service.
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