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--- |
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language: |
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- en |
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tags: |
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- audio-text-to-audio-text |
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- speech-understanding |
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- audio |
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- chat |
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license: apache-2.0 |
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datasets: |
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- custom |
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metrics: |
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- wer |
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- bleu |
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- AIR-Bench |
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--- |
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<div align="center"> |
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<h1> |
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EchoX: Towards Mitigating Acoustic-Semantic Gap via Echo Training for Speech-to-Speech LLMs |
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</h1> |
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</div> |
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<p align="center"> |
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<font size="3"> |
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<a href="https://github.com/FreedomIntelligence/EchoX">🐈⬛ Github</a> |  |
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<a href="https://arxiv.org/abs/2509.09174">📃 Paper</a> |  |
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<a href="https://huggingface.co/spaces/FreedomIntelligence/EchoX">🚀 Space</a> |  |
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<a href="https://huggingface.co/datasets/FreedomIntelligence/EchoX-Dialougues">📊 EchoX-Dialougues</a> |  |
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<a href="https://huggingface.co/datasets/KurtDu/EchoX-Dialogues-Plus">📊 EchoX-Dialogues-Plus</a> |
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</font> |
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</p> |
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## Model Description |
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EchoX is a Speech-to-Speech large language model that addresses the acoustic-semantic gap. By introducing **Echo Training**, EchoX integrates semantic and acoustic learning, mitigating the degradation of reasoning ability observed in existing speech-based LLMs. It is trained on only 10k hours of data while delivering state-of-the-art results in knowledge-based question answering and speech interaction tasks. |
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### Key Features |
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<div> |
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<ul> |
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<font size="3"><li>Mitigates Acoustic-Semantic Gap in Speech-to-Speech LLMs</li></font> |
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<font size="3"><li>Introduces Echo Training with a Novel Three-Stage Pipeline (S2T, T2C, Echo)</li></font> |
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<font size="3"><li>Trained on Only 10k Hours of Curated Data, Ensuring Efficiency</li></font> |
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<font size="3"><li>Achieves State-of-the-Art Performance in Knowledge-Based QA Benchmarks</li></font> |
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<font size="3"><li>Preserves Reasoning and Knowledge Abilities for Interactive Speech Tasks</li></font> |
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</ul> |
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</div> |
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## Usage |
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Load the EchoX model and run inference with your audio files as shown in the <a href="https://github.com/FreedomIntelligence/EchoX">GitHub repository</a>. |
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# <span>📖 Citation</span> |
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``` |
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@misc{zhang2025echoxmitigatingacousticsemanticgap, |
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title={EchoX: Towards Mitigating Acoustic-Semantic Gap via Echo Training for Speech-to-Speech LLMs}, |
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author={Yuhao Zhang and Yuhao Du and Zhanchen Dai and Xiangnan Ma and Kaiqi Kou and Benyou Wang and Haizhou Li}, |
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year={2025}, |
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eprint={2509.09174}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL}, |
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url={https://arxiv.org/abs/2509.09174}, |
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} |
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``` |