title: Perceptual Error Analysis of Human and Synthesized Voices.
abstract: OBJECTIVE
  To assess the quality of synthesized voices through listeners' skills in discriminating human and synthesized voices.
  
  
  METHODS
  Prospective study.
  
  
  METHODS
  Eighteen human voices with different types and degrees of deviation (roughness, breathiness, and strain, with three degrees of deviation: mild, moderate, and severe) were selected by three voice specialists. Synthesized samples with the same deviations of human voices were produced by the VoiceSim system. The manipulated parameters were vocal frequency perturbation (roughness), additive noise (breathiness), increasing tension, subglottal pressure, and decreasing vocal folds separation (strain). Two hundred sixty-nine listeners were divided in three groups: voice specialist speech language pathologists (V-SLPs), general clinician SLPs (G-SLPs), and naive listeners (NLs). The SLP listeners also indicated the type and degree of deviation.
  
  
  RESULTS
  The listeners misclassified 39.3% of the voices, both synthesized (42.3%) and human (36.4%) samples (P = 0.001). V-SLPs presented the lowest error percentage considering the voice nature (34.6%); G-SLPs and NLs identified almost half of the synthesized samples as human (46.9%, 45.6%). The male voices were more susceptible for misidentification. The synthesized breathy samples generated a greater perceptual confusion. The samples with severe deviation seemed to be more susceptible for errors. The synthesized female deviations were correctly classified. The male breathiness and strain were identified as roughness.
  
  
  CONCLUSIONS
  VoiceSim produced stimuli very similar to the voices of patients with dysphonia. V-SLPs had a better ability to classify human and synthesized voices. VoiceSim is better to simulate vocal breathiness and female deviations; the male samples need adjustment.
authors.affiliation: Universidade Federal de São Paulo, São Paulo, Brazil; Centro de Estudos da Voz-CEV, São Paulo, Brazil. Electronic address: marinaenglert@gmail.com.
authors.forename: Marina
authors.initials: M
authors.lastname: Englert
authors.affiliation: Centro de Estudos da Voz-CEV, São Paulo, Brazil.
authors.forename: Glaucya
authors.initials: G
authors.lastname: Madazio
authors.affiliation: Centro de Estudos da Voz-CEV, São Paulo, Brazil.
authors.forename: Ingrid
authors.initials: I
authors.lastname: Gielow
authors.affiliation: Universidade de Brasília, Brasília, Brazil.
authors.forename: Jorge
authors.initials: J
authors.lastname: Lucero
authors.affiliation: Universidade Federal de São Paulo, São Paulo, Brazil; Centro de Estudos da Voz-CEV, São Paulo, Brazil.
authors.forename: Mara
authors.initials: M
authors.lastname: Behlau
mesh_terms: D001307:Auditory Perception; D003143:Communication Devices for People with Disabilities; D005260:Female; D006801:Humans; D008297:Male; D011446:Prospective Studies; D013066:Speech-Language Pathology / Q000145:classification / Q000592:standards*; D014833:Voice Quality
keywords: Auditory perception; Judgment; Speech acoustic; Voice; Voice disorders