New framework translates spoken Nepali to emotion-conditioned sign language avatars

Researchers have developed NEST-V1, a novel multimodal framework designed for translating spoken Nepali words into emotion-conditioned sign language avatars. This pilot study focuses on four common Nepali words across three emotional states, demonstrating the feasibility of generating expressive sign language avatars. The system utilizes a shared acoustic encoder for simultaneous Automatic Speech Recognition and emotion classification, achieving high accuracy while maintaining parameter efficiency suitable for edge deployment. AI

IMPACT Establishes a technical foundation for real-time, emotionally expressive sign language communication systems for the hearing-impaired community.

RANK_REASON Academic paper detailing a new multimodal translation framework. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

• Nepali
• NEST-V1
• Sign Language

• paper
• model release

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