Make Patient Consultation Warmer: A Clinical Application for Speech Emotion Recognition
نویسندگان
چکیده
In recent years, many types of research have continued to improve the environment human speech and emotion recognition. As facial recognition has gradually matured through recognition, result this study provided more accurate complex emotional performance, identification will be derived from subjective interpretation into use computers automatically interpret speaker’s expression. Focused on in medical care, which can used understand current feelings physicians patients during a visit, treatment relationship between illness interaction. By transforming voice data single observation segment per second, first thirteenth dimensions frequency cestrum coefficients are as eigenvalue vectors. Vectors for vectors maximum, minimum, average, median, standard deviation, there 65 eigenvalues total construction an artificial neural network. The sentiment system developed by hospital is comparison results network classification, then foregoing comprehensive analysis interaction doctor patient. Using experimental module, rate 93.34%, accuracy 86.3%.
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ژورنال
عنوان ژورنال: Applied sciences
سال: 2021
ISSN: ['2076-3417']
DOI: https://doi.org/10.3390/app11114782