Browsing by Author "Orozco Arroyave, Juan Rafael"
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Item Acoustic characteristics of vot in plosive consonants produced by parkinson’s patients(Springer Science and Business Media Deutschland GmbH, 2020-09-01) Argüello Vélez, Patricia; Arias Vergara, Tomás; González Rátiva, María Claudia; Orozco Arroyave, Juan Rafael; Nöth, Elmar; Schuster, Maria ElkeVoice Onset Time (VOT) has been used as an acoustic measure for a better understanding of the impact of different motor speech disorders in speech production. The purpose of our paper is to present a methodology for the manual measuring of VOT in voiceless plosive sounds and to analyze its suitability to detect specific articulation problems in Parkinson’s disease (PD) patients. The experiments are performed with recordings of the diadochokinetic evaluation which consists in the rapid repetition of the syllables /pa-ta-ka/. A total of 50 PD patients and 50 healthy speakers (HC) participated in this study. Manual measurements include VOT values and also duration of the closure phase, duration of the consonant, and the maximum spectral energy during the burst phase. Results indicate that the methodology is consistent and allows the automatic classification between PD patients and healthy speakers with accuracies of up to 77% .Item Automatic detection of Voice Onset Time in voiceless plosives using gated recurrent units(Elsevier Inc., 2020-05-27) Arias Vergara, Tomás; Argüello Vélez, Patricia; Vásquez Correa, Juan Camilo; Nöth, Elmar; Schuster, Maria Elke; González Rátiva, María Claudia; Orozco Arroyave, Juan RafaelVoice Onset Time (VOT) has been used by researchers as an acoustic measure in order to gain some understanding about the impact of different motor speech disorders in speech production. However, VOT values are usually obtained manually, which is expensive and time consuming. In this paper we proposed a method for the automatic detection of VOT based on pre-trained Recurrent Neural Networks with Gated Recurrent Units (GRUs). Speech recordings from 50 Spanish native speakers from Colombia (25 male) are considered for the experiments. The recordings include the utterance of the diadochokinesis task /pa-ta-ka/ which is typically used for the evaluation of motor speech disorders like those caused due to Parkinson's disease. Additionally, the diadochokinesis task allows us to train a system to detect the VOT of voiceless plosive sounds in intermediate positions. Acoustic analysis is performed by extracting different temporal and spectral features from the recordings. According to the results, it is possible to detect the VOT with F1-score values of 0.66 for Image 1, 0.75 for Image 2, and 0.78 for Image 3 when the predicted values are compared with respect to the manual VOT labels.