--- library_name: transformers pipeline_tag: automatic-speech-recognition --- # ESRT: Edge-cloud Speech Recognition and Translation This repository contains the weights for ESRT-4B, as presented in the paper [Bandwidth-Efficient and Privacy-Preserving Edge-Cloud Many-to-Many Speech Translation](https://huggingface.co/papers/2605.28642). ESRT supports many-to-many speech-to-text translation across **45 languages** (45 × 44 directions). It uses an edge-cloud split inference architecture to protect voice privacy and reduce bandwidth by transmitting only compressed acoustic features instead of raw audio. - **Paper:** [arXiv:2605.28642](https://arxiv.org/abs/2605.28642) - **Code:** [https://github.com/yxduir/esrt](https://github.com/yxduir/esrt) [![arXiv](https://img.shields.io/badge/arXiv-2605.28642-b31b1b.svg)](https://arxiv.org/abs/2605.28642) [![Hugging Face Models](https://img.shields.io/badge/%F0%9F%A4%97-Models-yellow "https://huggingface.co/yxdu")](https://huggingface.co/yxdu/ESRT-4B) ## Timeline - **2026-05-29** — macOS CPU support added - **2026-05-28** — [ESRT-4B](https://huggingface.co/yxdu/ESRT-4B) has been released on Hugging Face with GPU support. ## Setup ```bash # Install uv (if not already installed) # curl -LsSf https://astral.sh/uv/install.sh | sh git clone https://github.com/yxduir/ESRT cd ESRT uv venv --python 3.10 source .venv/bin/activate uv pip install -r requirements.txt # uv pip install -r requirements_mac.txt ``` > **Note**: The GPU setup includes `vllm`. macOS uses a CPU backend with `transformers`. ## Test Data ```bash hf download --repo-type dataset yxdu/fleurs_eng_test --local-dir ./fleurs_eng_test ``` ## Inference Two-stage inference: edge side and cloud side. ```bash #Offline for performance evaluation. #Total 45x44 directions, this is a demo for English->44. bash run_eng_44.sh #bash run_test_mac.sh #Online deployment guide coming soon. ``` > **Note**: The GPU only supports 'bf16' inference. ## Training Training code will be open-sourced in a future release. Validated on: - **GPU**: NVIDIA A100 80GB × 8 - **NPU**: Huawei Ascend 910C 64GB × 8 ## Supported Languages | Family | Languages | | ------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Afro-Asiatic | Arabic, Hebrew | | Austroasiatic | Khmer, Vietnamese | | Austronesian | Indonesian, Malay, Tagalog | | Dravidian | Tamil | | Indo-European | Bengali, Bulgarian, Catalan, Czech, Danish, Dutch, English, French, German, Greek, Hindi, Croatian, Italian, Norwegian, Persian, Polish, Portuguese, Romanian, Russian, Slovak, Slovenian, Spanish, Swedish, Urdu | | Japonic | Japanese | | Koreanic | Korean | | Kra–Dai | Lao, Thai | | Sino-Tibetan | Chinese, Burmese, Cantonese | | Turkic | Azerbaijani, Kazakh, Turkish, Uzbek | | Uralic | Finnish, Hungarian | ## Citation ```bibtex @misc{du2026bandwidthefficientprivacypreservingedgecloudmanytomany, title={Bandwidth-Efficient and Privacy-Preserving Edge-Cloud Many-to-Many Speech Translation}, author={Yexing Du and Kaiyuan Liu and Youcheng Pan and Bo Yang and Ming Liu and Bing Qin and Yang Xiang}, year={2026}, eprint={2605.28642}, archivePrefix={arXiv}, primaryClass={cs.AI}, url={https://arxiv.org/abs/2605.28642}, } ```