Low Resource Multimodal Translation of Nepali Spoken Words into Emotion-Conditioned Sign Language Avatars

arXiv:2606.26107v1 Announce Type: cross Abstract: Sign language communication systems, that integrate emotional expression remain underexplored, particularly for low-resource languages. This pilot study presents NEST-V1 (Nepali Emotion and Speech Transformer - Version 1), a proof-of-concept multimodal framework that demonstrates the feasibility of generating emotion-conditioned Nepali Sign Language avatars from spoken input. As a preliminary investigation, we focus on four common Nepali words ("thank you", "hello", "house", "me") across three emotional states (happy, neutral, sad) to validate

Source: arXiv cs.AI — read the full report at the original publisher.

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