This study investigates the human translation process from English to Czech in a multi-modal scenario (images) using reaction times. We make a distinction between ambiguous and unambiguous sentences where in the former, more information would be needed in order to make a proper translation (e.g. gender of the subject). Simultaneously, we also provide visual aid to help in disambiguation, which is necessary for the ambiguous sentences. We confirm that ambiguous sentences take longer to translate and the provision of disambiguating visual aid slows the translation process. When provided with an unrelated visual aid, humans are able to recognize and spend less time on it but still significantly more than in other conditions. These findings are a clear manifestation of the Stroop effect (longer processing times for incongruent combinations).
The Shannon game has long been used as a thought experiment in linguistics and NLP, asking participants to guess the next letter in a sentence based on its preceding context. We extend the game by introducing an optional extra modality in the form of image information. To investigate the impact of multimodal information in this game, we use human participants and a language model (LM, GPT-2).We show that the addition of image information improves both self-reported confidence and accuracy for both humans and LM. Certain word classes, such as nouns and determiners, benefit more from the additional modality information. The priming effect in both humans and the LM becomes more apparent as the context size (extra modality information + sentence context) increases. These findings highlight the potential of multimodal information in improving language understanding and modeling.
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