Assessment of speech intelligibility in Parkinson's disease using a speech-to-text system

Patients with Parkinson's disease may have difficulties in speaking because of reduced coordination of the muscles that control breathing, phonation, articulation and prosody. Symptoms that may occur are weakening of the volume of the voice, voice monotony, changes in the quality of the voice, the speed of speech, uncontrolled repetition of words, and difficult speech intelligibility. To date, evaluation of the speech intelligibility is performed based on the Unified Parkinson's Disease Rating Scale (UPDRS). Specifically, section 3.1 (eloquence) of the cited scale provides the specialist with some tips to evaluate the patient's speech ability. With the aim of evaluating the speech intelligibility by measuring the variation in parameters in an objective manner, we show that a speech-to-text (STT) system could help specialists to obtain an accurate and objective measure of speech, phrase and word intelligibility in Parkinson’s disease. STT systems are based on methodologies and technologies that enable the recognition and translation of spoken language into text by computers and computerized devices. We decided to base our study on Google Speech to Text conversion. We expand Voxtester, a software system for digital assessment of voice and speech changes in Parkinson disease, in order to perform this study. No previous studies have been presented to address the mentioned challenges based on STT. The experiments here presented are related with detection/classification between pathological speech from patients with PD and regular speech from healthy control group. The results are very interesting and are an important step towards assessing the intelligibility of the speech of PD patients.