Digitised evaluation of speech intelligibility using vowels in maxillectomy patients.

Among the functional disabilities that patients face following maxillectomy, speech impairment is a major factor influencing quality of life. Proper rehabilitation of speech, which may include prosthodontic and surgical treatments and speech therapy, requires accurate evaluation of speech intelligibility (SI). A simple, less time-consuming yet accurate evaluation is desirable both for maxillectomy patients and the various clinicians providing maxillofacial treatment. This study sought to determine the utility of digital acoustic analysis of vowels for the prediction of SI in maxillectomy patients, based on a comprehensive understanding of speech production in the vocal tract of maxillectomy patients and its perception. Speech samples were collected from 33 male maxillectomy patients (mean age 57.4 years) in two conditions, without and with a maxillofacial prosthesis, and formant data for the vowels /a/,/e/,/i/,/o/, and /u/ were calculated based on linear predictive coding. The frequency range of formant 2 (F2) was determined by differences between the minimum and maximum frequency. An SI test was also conducted to reveal the relationship between SI score and F2 range. Statistical analyses were applied. F2 range and SI score were significantly different between the two conditions without and with a prosthesis (both P < .0001). F2 range was significantly correlated with SI score in both the conditions (Spearman's r = .843, P < .0001; r = .832, P < .0001, respectively). These findings indicate that calculating the F2 range from 5 vowels has clinical utility for the prediction of SI after maxillectomy.

Evaluation of articulation simulation system using artificial maxillectomy models.

Acoustic evaluation is valuable for guiding the treatment of maxillofacial defects and determining the effectiveness of rehabilitation with an obturator prosthesis. Model simulations are important in terms of pre-surgical planning and pre- and post-operative speech function. This study aimed to evaluate the acoustic characteristics of voice generated by an articulation simulation system using a vocal tract model with or without artificial maxillectomy defects. More specifically, we aimed to establish a speech simulation system for maxillectomy defect models that both surgeons and maxillofacial prosthodontists can use in guiding treatment planning. Artificially simulated maxillectomy defects were prepared according to Aramany's classification (Classes I-VI) in a three-dimensional vocal tract plaster model of a subject uttering the vowel /a/. Formant and nasalance acoustic data were analysed using Computerized Speech Lab and the Nasometer, respectively. Formants and nasalance of simulated /a/ sounds were successfully detected and analysed. Values of Formants 1 and 2 for the non-defect model were 675.43 and 976.64 Hz, respectively. Median values of Formants 1 and 2 for the defect models were 634.36 and 1026.84 Hz, respectively. Nasalance was 11% in the non-defect model, whereas median nasalance was 28% in the defect models. The results suggest that an articulation simulation system can be used to help surgeons and maxillofacial prosthodontists to plan post-surgical defects that will be facilitate maxillofacial rehabilitation.