Epidemiological studies suggest that lifetime prevalence of voice disorders is about 30% for the general adult population. Moreover, vocal performance degradation may be amongst the earliest indicators of a neurodegenerative disease onset, such as Parkinson's disease. Lacking alternative cost-effective biomarkers, biomedical speech signal processing has been gaining increasing impetus towards developing clinical decision support tools. Acoustic analysis of speech signals provides a convenient, automatic, accurate, robust, inexpensive, scalable approach assisting medical diagnosis and symptom severity monitoring. Nevertheless, the algorithmic tools developed for biomedical speech signal processing are spread across different software platforms, hindering direct algorithmic comparisons and the further development of this impending field. This study brings many biomedical speech signal processing algorithms together under the same software platform, and has led to the development of a practical free toolkit which can be accessed over the Internet using a simple application.