Background: Vocal loading tasks (VLT) are important tools in voice assessment. Current research shows varied and inconsistent results, potentially due to differences in VLT implementation. These inconsistencies, coupled with limited standardized protocols and restricted accessibility to testing tools, have impeded large-scale studies and clinical applications. There is a need for standardized, accessible software to improve protocol repeatability and facilitating clinical implementation.

Methods: The software development followed an open-source approach using PsychoPy, a Python-based platform for behavioral experiments. Development focused on creating modular components for pre-loading assessment, loading tasks, and post-loading evaluation. The software was tested across multiple operating systems, user groups, settings (both research and clinical), and languages to ensure broad applicability.

Results: The developed software provides configurable vocal loading tasks, such as background noise conditions or loudness targets, and includes a range of stimuli like reading tasks, mock lectures, and language-independent picture descriptions. Data collection includes pre- and post-loading voice recordings, which are automatically segmented for analysis. Voice analysis is performed using Parselmouth, which enables automated computation of the Acoustic Voice Quality Index (AVQI) and other acoustic measures using Praat. The software runs on standard computing hardware and includes tools for data processing and analysis, making it suitable for both research and clinical applications.

Conclusions: This software addresses fundamental needs in vocal loading research by providing a standardized yet flexible implementation platform. Its open-source, modular design and automated voice analysis capabilities make it a valuable tool for advancing vocal loading research and clinical assessment. The protocol represents a significant step toward establishing consistent methodology in voice research while maintaining adaptability for various applications.