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As two of the five traditional human senses (sight, hearing, taste, smell,and touch), vision and sound are basic sources through which humans understandthe world. Often correlated during natural events, these two modalities combineto jointly affect human perception. In this paper, we pose the task ofgenerating sound given visual input. Such capabilities could help enableapplications in virtual reality (generating sound for virtual scenesautomatically) or provide additional accessibility to images or videos forpeople with visual impairments. As a first step in this direction, we applylearning-based methods to generate raw waveform samples given input videoframes. We evaluate our models on a dataset of videos containing a variety ofsounds (such as ambient sounds and sounds from people/animals). Our experimentsshow that the generated sounds are fairly realistic and have good temporalsynchronization with the visual inputs.

Visual to Sound: Generating Natural Sound for Videos in the Wild