从呼吸音中分离年龄影响,发现非年龄相关声学信号可用于慢阻肺筛查。
Separating Voice from Age in COPD Screening
- 基于个体级别重复采样,隔离年龄与性别干扰因素。
- 剔除年龄后模型仍达0.717的AUC,说明存在非年龄声学特征。
- 现有评估方法无法区分信号真伪,需改进实验设计。
语音被提出作为慢性阻塞性肺病(COPD)低成本筛查信号。由于COPD与年龄强相关,且语音随年龄变化,此类结果可能仅由年龄解释。我们采用严格个体级协议重新评估一个公开的持续发声语料库(1246条录音,68名参与者)。通过多次年龄匹配的样本集评估混杂因素自身的表现。原始年龄(0.510 [0.469, 0.551])和性别(0.479)在随机水平上表现,而排除年龄的声学模型仍取得ROC-AUC 0.717 [0.552, 0.859] 和平均精度0.747 [0.581, 0.892],优于0.5基准。包含年龄的模型性能降至0.531–0.679。两个固定超参的学习器复现了该分离效果。研究发现:含年龄训练的模型在年龄均衡目标集上迁移能力更差;14个经典声学质量指标的判别力与55维联合表示相当。结论为:存在非年龄声学信号,但释放特征中无法排除录音条件混杂,且标准评估协议无法区分这些可能性。
原文摘要 · Abstract (English)
Voice has been proposed as a low-cost screening signal for chronic obstructive pulmonary disease (COPD). COPD is strongly age-associated and voice changes with age, thus such results admit a trivial alternative explanation. We re-evaluate a public sustained-phonation corpus ($1246$ recordings, $68$ participants) under a strictly participant-level protocol. We therefore evaluate on repeatedly drawn age-matched cohorts and report the discrimination achieved by the confounders themselves on those same cohorts. Where raw (unmodelled) age ($0.510$ $[0.469, 0.551]$) and raw gender ($0.479$) are both measured at chance, acoustic models excluding age retain ROC-AUC $0.717$ $[0.552, 0.859]$ and average precision $0.747$ $[0.581, 0.892]$ against a one-to-one baseline of $0.5$, whereas models containing age fall to $0.531$--$0.679$. The separation is reproduced by two further learners with fixed hyperparameters. Two findings have broader methodological implications: models trained with age transfer less effectively to an age-balanced target cohort than otherwise identical models trained without age, and fourteen classical voice-quality and perturbation measures achieve comparable discrimination to a $55$-dimensional combined representation. We conclude that a non-age acoustic signal is present, that confounding by recording conditions cannot be excluded from the released features, and that the evaluation protocol in standard use cannot distinguish these possibilities.
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