标题： 使用神经音频编解码器作为基础模型的噪声中实时喉部麦克风语音增强 显示英文标题

标题： Real-time speech enhancement in noise for throat microphone using neural audio codec as foundation model

摘要： 我们展示了一个使用喉部麦克风捕捉的语音实时增强演示。 该演示旨在展示完整的流程，从录音到基于深度学习的后处理，适用于通过体传导麦克风在嘈杂环境中捕捉的语音。 喉部麦克风记录皮肤振动，这会自然地衰减外部噪声，但这种鲁棒性是以减少音频带宽为代价的。 为了解决这一挑战，我们在Vibravox数据集上微调Kyutai的Mimi——一种支持实时推理的神经音频编解码器——该数据集包含成对的空气传导和喉部麦克风录音。 我们将这种增强策略与最先进模型进行比较，并证明其性能更优。 推理在交互式界面中运行，允许用户切换增强功能、可视化频谱图并监控处理延迟。 显示英文摘要

摘要： We present a real-time speech enhancement demo using speech captured with a throat microphone. This demo aims to showcase the complete pipeline, from recording to deep learning-based post-processing, for speech captured in noisy environments with a body-conducted microphone. The throat microphone records skin vibrations, which naturally attenuate external noise, but this robustness comes at the cost of reduced audio bandwidth. To address this challenge, we fine-tune Kyutai's Mimi--a neural audio codec supporting real-time inference--on Vibravox, a dataset containing paired air-conducted and throat microphone recordings. We compare this enhancement strategy against state-of-the-art models and demonstrate its superior performance. The inference runs in an interactive interface that allows users to toggle enhancement, visualize spectrograms, and monitor processing latency.