Perceptual Error Identification of Human and Synthesized Voices

SummaryObjectives/HypothesisTo verify the discriminatory ability of human and synthesized voice samples.Study DesignThis is a prospective study.MethodsA 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).ResultsThe 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).ConclusionsThe 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.