用噪声环境下的助听器语音数据，提升语音控制的抗干扰能力
Noise-Robust Hearing Aid Voice Control
- 构建了含三种麦克风的助听器噪声语音数据集
- 骨传导语音配合外置麦克风可显著提升识别率
- 适合研究语音增强与助听器交互的开发者
提升助听器语音控制的鲁棒性对提高听力障碍者使用率和用户体验至关重要。本文首先提出一个新型助听器语音数据集，包含由2个耳后式（BTE）和1个耳道式（IEC）麦克风采集的噪声环境下个人语音。其次，评估了轻量级、前沿的关键字检测模型在不同麦克风信号组合下的基线性能。实验表明，利用带宽受限的耳道式骨传导语音（BCS）能有效实现噪声鲁棒的助听器语音控制；同时，通过外置耳后式麦克风提供的宽带信号辅助，语音控制性能进一步提升。为推动该领域持续发展，本研究公开了该助听器噪声语音数据集。
原文摘要 · Abstract (English)
Advancing the design of robust hearing aid (HA) voice control is crucial to increase the HA use rate among hard of hearing people as well as to improve HA users' experience. In this work, we contribute towards this goal by, first, presenting a novel HA speech dataset consisting of noisy own voice captured by 2 behind-the-ear (BTE) and 1 in-ear-canal (IEC) microphones. Second, we provide baseline HA voice control results from the evaluation of light, state-of-the-art keyword spotting models utilizing different combinations of HA microphone signals. Experimental results show the benefits of exploiting bandwidth-limited bone-conducted speech (BCS) from the IEC microphone to achieve noise-robust HA voice control. Furthermore, results also demonstrate that voice control performance can be boosted by assisting BCS by the broader-bandwidth BTE microphone signals. Aiming at setting a baseline upon which the scientific community can continue to progress, the HA noisy speech dataset has been made publicly available.
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