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About this paper
Ngoc Dung Huynh, Mohamed Reda Bouadjenek, Imran Razzak, Hakim Hacid, Sunil Aryal
The authors introduce SVLA, a system that combines speech, vision, and language in a token-based model, with image features supplied by a visual encoder. For complex spoken answers, an instruction-based variant first generates text to guide speech. On COCO-2014, it scores 62.2 CIDEr for image-plus-speech input and speech output, versus 2.0 for direct generation; this does not establish natural audio.
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