Marina Englert1, Glaucya Madazio2, Ingrid Gielow2, Jorge Lucero3, Mara Behlau4. 1. Department of Speech Language Pathology and Audiology, Universidade Federal de São Paulo, São Paulo, Brazil; Voice Department, Centro de Estudos da Voz-CEV, São Paulo, Brazil. Electronic address: marinaenglert@gmail.com. 2. Voice Department, Centro de Estudos da Voz-CEV, São Paulo, Brazil. 3. Universidade de Brasília, Brasília, Brazil. 4. Department of Speech Language Pathology and Audiology, Universidade Federal de São Paulo, São Paulo, Brazil; Voice Department, Centro de Estudos da Voz-CEV, São Paulo, Brazil.
Abstract
OBJECTIVES/HYPOTHESIS: To verify the discriminatory ability of human and synthesized voice samples. STUDY DESIGN: This is a prospective study. METHODS: A total of 70 subjects, 20 voice specialist speech-language pathologists (V-SLPs), 20 general SLPs (G-SLPs), and 30 naive listeners (NLs) participated of a listening task that was simply to classify the stimuli as human or synthesized. Samples of 36 voices, 18 human and 18 synthesized vowels, male and female (9 each), with different type and degree of deviation, were presented with 50% of repetition to verify intrarater consistency. Human voices were collected from a vocal clinic database. Voice disorders were simulated by perturbations of vocal frequency, jitter (roughness), additive noise (breathiness) and by increasing tension and decreasing separation of the vocal folds (strain). RESULTS: The average amount of error considering all groups was 37.8%, 31.9% for V-SLP, 39.3% for G-SLP, and 40.8% for NL. V-SLP had smaller mean percentage error for synthesized (24.7%), breathy (36.7%), synthesized breathy (30.8%), and tense (25%) and female (27.5%) voices. G-SLP and NL presented equal mean percentage error for all voices classification. All groups together presented no difference on the mean percentage error between human and synthesized voices (P value = 0.452). CONCLUSIONS: The quality of synthesized samples was very high. V-SLP presented a lower amount of error, which allows us to infer that auditory training assists on vocal analysis tasks.
OBJECTIVES/HYPOTHESIS: To verify the discriminatory ability of human and synthesized voice samples. STUDY DESIGN: This is a prospective study. METHODS: A total of 70 subjects, 20 voice specialist speech-language pathologists (V-SLPs), 20 general SLPs (G-SLPs), and 30 naive listeners (NLs) participated of a listening task that was simply to classify the stimuli as human or synthesized. Samples of 36 voices, 18 human and 18 synthesized vowels, male and female (9 each), with different type and degree of deviation, were presented with 50% of repetition to verify intrarater consistency. Human voices were collected from a vocal clinic database. Voice disorders were simulated by perturbations of vocal frequency, jitter (roughness), additive noise (breathiness) and by increasing tension and decreasing separation of the vocal folds (strain). RESULTS: The average amount of error considering all groups was 37.8%, 31.9% for V-SLP, 39.3% for G-SLP, and 40.8% for NL. V-SLP had smaller mean percentage error for synthesized (24.7%), breathy (36.7%), synthesized breathy (30.8%), and tense (25%) and female (27.5%) voices. G-SLP and NL presented equal mean percentage error for all voices classification. All groups together presented no difference on the mean percentage error between human and synthesized voices (P value = 0.452). CONCLUSIONS: The quality of synthesized samples was very high. V-SLP presented a lower amount of error, which allows us to infer that auditory training assists on vocal analysis tasks.
Authors: Leonardo Wanderley Lopes; Jonas Almeida de Freitas; Anna Alice Almeida; Priscila Oliveira Costa Silva; Giorvan Ânderson Dos Santos Alves Journal: Braz J Otorhinolaryngol Date: 2017-07-05