论文标题
区分慢性阻塞性肺疾病患者的言语前后治疗
Distinguishing between pre- and post-treatment in the speech of patients with chronic obstructive pulmonary disease
论文作者
论文摘要
慢性阻塞性肺疾病（COPD）引起肺部炎症和气流阻塞，导致各种呼吸道症状。这也是死亡的主要原因，影响了世界各地数百万个人。患者通常需要治疗和住院治疗，而目前尚无治愈。由于COPD主要影响呼吸系统，因此言语和非语言发声是衡量治疗作用的主要途径。 In this work, we present results on a new COPD dataset of 20 patients, showing that, by employing personalisation through speaker-level feature normalisation, we can distinguish between pre- and post-treatment speech with an unweighted average recall (UAR) of up to 82\,\% in (nested) leave-one-speaker-out cross-validation.我们进一步确定了最重要的特征，并将其链接到病理语音特性，从而实现了治疗效果的听觉解释。基于这种方法的监测工具可能有助于客观化COPD患者的临床状况并促进个性化治疗计划。
Chronic obstructive pulmonary disease (COPD) causes lung inflammation and airflow blockage leading to a variety of respiratory symptoms; it is also a leading cause of death and affects millions of individuals around the world. Patients often require treatment and hospitalisation, while no cure is currently available. As COPD predominantly affects the respiratory system, speech and non-linguistic vocalisations present a major avenue for measuring the effect of treatment. In this work, we present results on a new COPD dataset of 20 patients, showing that, by employing personalisation through speaker-level feature normalisation, we can distinguish between pre- and post-treatment speech with an unweighted average recall (UAR) of up to 82\,\% in (nested) leave-one-speaker-out cross-validation. We further identify the most important features and link them to pathological voice properties, thus enabling an auditory interpretation of treatment effects. Monitoring tools based on such approaches may help objectivise the clinical status of COPD patients and facilitate personalised treatment plans.
