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@ARTICLE{Orozco-Arroyave_DSP_2017,
         author = {Orozco-Arroyave, Juan Rafael and Vasquez-Correa, Juan Camilo and Vargas-Bonilla, Jes{\'{u}}s Francisco and Arora, Raman and Dehak, Najim and Nidadavolu, Phani Sankar and Christensen, Heidi and Rudzicz, Frank and Yancheva, Maria and Vann, Alyssa and Vogler, Nikolai and Bocklet, Tobias and Cernak, Milos and Hannink, Julius and N{\"{o}}th, Elmar},
       keywords = {Articulation, Dysarthria, intelligibility, Parkinson's disease, Phonation, prosody, python, software, speech processing},
       projects = {Idiap},
          title = {NeuroSpeech: An open-source software for Parkinson's speech analysis},
        journal = {Digital Signal Processing},
           year = {2017},
            doi = {10.1016/j.dsp.2017.07.004},
       abstract = {A new software for modeling pathological speech signals is presented in this paper. The software is called NeuroSpeech. This software enables the analysis of pathological speech signals considering different speech dimensions: phonation, articulation, prosody, and intelligibility. All the methods considered in the software have been validated in previous experiments and publications. The current version of NeuroSpeech was developed to model dysarthric speech signals from people with Parkinson's disease; however, the structure of the software allows other computer scientists or developers to include other pathologies and/or other measures in order to complement the existing options. Three different tasks can be performed with the current version of the software: (1) the modeling of the speech recordings considering the aforementioned speech dimensions, (2) the automatic discrimination of Parkinson's vs. non-Parkinson's speech signals (if the user has access to recordings of other pathologies, he/she can re-train the system to perform the detection of other diseases), and (3) the prediction of the neurological state of the patient according to the Unified Parkinson's Disease Rating Scale (UPDRS) score. The prediction of the dysarthria level according to the Frenchay Dysarthria Assessment scale is also provided (the user can also train the system to perform the prediction of other kind of scales or degrees of severity).

To the best of our knowledge, this is the first software with the characteristics described above, and we consider that it will help other researchers to contribute to the state-of-the-art in pathological speech assessment from different perspectives, e.g., from the clinical point of view for interpretation, and from the computer science point of view enabling the test of different measures and pattern recognition techniques.}
}