IsoSignVid2Aud: Sign Language Video to Audio Conversion without Text Intermediaries
October 09, 2025 ยท Declared Dead ยท ๐ International Conference on AI-ML-Systems
Repo contents: README.md
Authors
Harsh Kavediya, Vighnesh Nayak, Bheeshm Sharma, Balamurugan Palaniappan
arXiv ID
2510.07837
Category
cs.CV: Computer Vision
Cross-listed
cs.MM,
cs.SD
Citations
0
Venue
International Conference on AI-ML-Systems
Repository
https://github.com/BheeshmSharma/IsoSignVid2Aud_AIMLsystems-2025
Last Checked
1 month ago
Abstract
Sign language to spoken language audio translation is important to connect the hearing- and speech-challenged humans with others. We consider sign language videos with isolated sign sequences rather than continuous grammatical signing. Such videos are useful in educational applications and sign prompt interfaces. Towards this, we propose IsoSignVid2Aud, a novel end-to-end framework that translates sign language videos with a sequence of possibly non-grammatic continuous signs to speech without requiring intermediate text representation, providing immediate communication benefits while avoiding the latency and cascading errors inherent in multi-stage translation systems. Our approach combines an I3D-based feature extraction module with a specialized feature transformation network and an audio generation pipeline, utilizing a novel Non-Maximal Suppression (NMS) algorithm for the temporal detection of signs in non-grammatic continuous sequences. Experimental results demonstrate competitive performance on ASL-Citizen-1500 and WLASL-100 datasets with Top-1 accuracies of 72.01\% and 78.67\%, respectively, and audio quality metrics (PESQ: 2.67, STOI: 0.73) indicating intelligible speech output. Code is available at: https://github.com/BheeshmSharma/IsoSignVid2Aud_AIMLsystems-2025.
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