title: Automatic intelligibility assessment of speakers after laryngeal cancer by means of acoustic modeling.
abstract: OBJECTIVE
  One aspect of voice and speech evaluation after laryngeal cancer is acoustic analysis. Perceptual evaluation by expert raters is a standard in the clinical environment for global criteria such as overall quality or intelligibility. So far, automatic approaches evaluate acoustic properties of pathologic voices based on voiced/unvoiced distinction and fundamental frequency analysis of sustained vowels. Because of the high amount of noisy components and the increasing aperiodicity of highly pathologic voices, a fully automatic analysis of fundamental frequency is difficult. We introduce a purely data-driven system for the acoustic analysis of pathologic voices based on recordings of a standard text.
  
  
  METHODS
  Short-time segments of the speech signal are analyzed in the spectral domain, and speaker models based on this information are built. These speaker models act as a clustered representation of the acoustic properties of a person's voice and are thus characteristic for speakers with different kinds and degrees of pathologic conditions. The system is evaluated on two different data sets with speakers reading standardized texts. One data set contains 77 speakers after laryngeal cancer treated with partial removal of the larynx. The other data set contains 54 totally laryngectomized patients, equipped with a Provox shunt valve. Each speaker was rated by five expert listeners regarding three different criteria: strain, voice quality, and speech intelligibility.
  
  
  CONCLUSIONS
  We show correlations for each data set with r and ρ≥0.8 between the automatic system and the mean value of the five raters. The interrater correlation of one rater to the mean value of the remaining raters is in the same range. We thus assume that for selected evaluation criteria, the system can serve as a validated objective support for acoustic voice and speech analysis.
authors.affiliation: Department of Phoniatrics and Pediatric Audiology, University Hospital Erlangen, Erlangen, Germany. tobias.bocklet@informatik.uni-erlangen.de
authors.forename: Tobias
authors.initials: T
authors.lastname: Bocklet
authors.forename: Korbinian
authors.initials: K
authors.lastname: Riedhammer
authors.forename: Elmar
authors.initials: E
authors.lastname: Nöth
authors.forename: Ulrich
authors.initials: U
authors.lastname: Eysholdt
authors.forename: Tino
authors.initials: T
authors.lastname: Haderlein
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001331:Automation; D005858:Germany; D006801:Humans; D007822:Laryngeal Neoplasms / Q000150:complications / Q000503:physiopathology / Q000601:surgery*; D007825:Laryngectomy / Q000009:adverse effects; D007831:Larynx, Artificial; D008875:Middle Aged; D015233:Models, Statistical; D015588:Observer Variation; D011237:Predictive Value of Tests; D011932:Reading; D012044:Regression Analysis; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted; D013061:Speech Acoustics; D013065:Speech Intelligibility; D013068:Speech Production Measurement / Q000379:methods*; D013071:Speech, Alaryngeal / Q000295:instrumentation; D013997:Time Factors; D016896:Treatment Outcome; D014832:Voice Disorders / Q000175:diagnosis / Q000209:etiology / Q000503:physiopathology / Q000601:surgery*; D014833:Voice Quality