用于嗓音治疗练习的语音数据集的开发与评估：定量音频分析和用户反馈的横断面研究。

文献信息

中文摘要

目的： 本研究旨在使用标准化的视频引导录音方案，开发并验证一个用于发声困难治疗的高质量语音数据集，该方案包含一系列治疗性嗓音练习。该数据集旨在支持数字健康应用的开发，以实现具有实时生物反馈的家庭嗓音训练，从而应对言语语言病理学当前的挑战，包括治疗可及性有限以及对可扩展、以患者为中心的干预措施的需求。
方法： 从成年参与者中收集了一个语音数据集，参与者在标准化条件下通过智能手机和耳内麦克风录制德语嗓音治疗练习。除声学数据收集外，参与者还评估了录音程序和视频引导的练习说明。使用Praat对音高（Hz）、强度（dB）和倒频谱峰值突出度（CPP）进行声学分析，数据按年龄和性别分组。进行相关性分析以评估参与者和练习之间录音的一致性。
结果： 所得数据集包含175名成年人的录音，总计约6.6 GB的音频数据，其中一部分作为开放获取提供。参与者报告对录音程序和教学视频的总体接受度很高，同时也指出了需要改进的方面，特别是在节奏和清晰度方面。声学和相关性分析显示，CPP、音高和强度存在练习特异性变化，以及年龄和性别组之间的系统性差异，表明数据集中既存在变异性又具有结构一致性。
结论： 该数据集代表了数字嗓音治疗的一种新资源，特别是由于其专注于德语的结构化治疗性练习。它为开发和评估旨在增强自我管理嗓音训练并在临床环境之外支持治疗过程的数字健康应用提供了坚实的基础。

英文摘要

PURPOSE: This study aims to develop and validate a high-quality voice dataset for dysphonia therapy using a standardized, video-guided recording protocol comprising a range of therapeutic voice exercises. The dataset is designed to support the development of digital health applications that enable home-based voice training with real-time biofeedback, thereby addressing current challenges in speech-language pathology, including limited access to therapy and the need for scalable, patient-centered interventions.
METHODS: A voice dataset was collected from adult participants performing voice therapy exercises in German, recorded via smartphone and in-ear microphones under standardized conditions. In addition to acoustic data collection, participants evaluated the recording procedure and video-guided exercise instructions. Acoustic analyses of pitch (Hz), intensity (dB), and Cepstral Peak Prominence (CPP) were conducted using Praat, with data grouped by age and sex. Correlation analyses were performed to assess the consistency of recordings across participants and exercises.
RESULTS: The resulting dataset comprises recordings from 175 adults, totaling approximately 6.6 GB of audio data, with a subset made available as open access. Participants reported high overall acceptance of the recording procedure and instructional videos, while also identifying areas for improvement, particularly regarding pacing and clarity. Acoustic and correlation analyses demonstrated exercise-specific variations in CPP, pitch and intensity, as well as systematic differences across age and gender groups, indicating both variability and structured consistency within the dataset.
CONCLUSION: The dataset represents a novel resource for digital voice therapy, particularly due to its focus on structured therapeutic exercises in German. It provides a robust foundation for the development and evaluation of digital health applications aimed at enhancing self-managed voice training and supporting therapy processes beyond clinical settings.