Enhancing Natural Language Understanding through Cross-Modal Interaction: Meaning Recovery from Acoustically Noisy Speech

Abstract

Cross-modality between vision and language is a key component for effective and efficient communication, and human language processing mechanism successfully integrates information from various modalities to extract the intended meaning. However, incomplete linguistic input, i.e. due to a noisy environment, is one of the challenges for a successful communication. In that case, an incompleteness in one channel can be compensated by information from another one. In this paper, by conducting visual-world paradigm, we investigated the dynamics between syntactically possible gap fillers and the visual arrangements in incomplete German sentences and their effect on overall sentence interpretation.

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