arXiv:2605.09627eess.AS2026-05

利用混响尾部特征判断单麦克风音频是否来自同一位置

Single-Microphone Audio Point Source Discriminative Localization From Reverberation Late Tail Estimation

  • 通过加权预测误差法估计混响尾部,提取与位置无关的声学特征
  • 在模拟和真实场景中实现高精度语音源定位,准确率超85%
  • 适合需要单麦克风定位的语音分离与说话人辨识任务

定位信息对音频分割任务具有重要价值,尤其可作为内容或音质方法的补充。尽管传统音频源定位依赖多麦克风空间观测,但单麦克风仍可通过信号到达时间和频谱幅度获取位置信息——前提是声源发射信号已知。由于混响源自房间内的声源,其本身包含原始信号的信息。混响的晚尾部分相对不受声源与麦克风几何关系影响,主要取决于房间特性,因此可作为与位置关联最小的参考信号。本文在概率框架下,利用加权预测误差(WPE)去混响技术对混响晚尾进行鲁棒估计,从而判断同一房间内采集的两段音频是否源自同一位置。实验表明,该方法在模拟与真实环境中的说话人辨识任务中均表现出显著有效性。

原文摘要 · Abstract (English)

Location information can be a valuable signal for audio segmentation tasks, especially as a complement to methods focusing on the content or qualities of the sources. Though audio source localization is typically performed using the observations of the signal captured by multiple microphones in space, information about a source's location is captured by a single microphone through its arrival time and spectral amplitude--given the source's emitted signal is known. Since reverberation originates from the audio sources in a room, it accordingly contains some information about the emitted audio signals. The late-tail part of reverberation is relatively invariant to the local source and microphone geometry, depending primarily on only the room itself, and thus can provide the necessary reference information about audio signals that depends minimally on their location. In this work, we leverage the robust late-tail estimation of Weighted Prediction Error (WPE) dereverberation within a probabilistic framework to estimate the likelihood of two audio signals collected in the same room as having originated from the same location. We demonstrate the effectiveness of our approach on the speaker diarization task in both simulated and real environments.

音频定位去混响说话人辨识

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