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Purpose This research gathered pilot data on the effects of a typical collegiate athletic season on the male coach's voice. Materials and methods Ten male coaches and ten age- and sex-matched controls participated. Qualitative and quantitative analyses were performed to assess group differences in: 1) written self-reports obtained during one session, 2) acoustic and aerodynamic variables obtained during regular season and during off-season for the coaches and only once for the controls, and 3) auditory-perceptual data provided by three speech-language pathologists using the Consensus Auditory-Perceptual Evaluation of Voice during one listening session. Data pertaining to the coaches’ regular season, to the coaches’ off-season, and to the control participants were designated as in-season, off-season, and control, respectively. Results Significant self-reported findings included more phonotraumatic behaviors in the coaches than in the controls and higher in-season than off-season and control vocal demand. The coaches’ history of voice problems was unrelated and the controls’ was related to respiratory illness and addressing a large audience. A significant acoustic finding was lower off-season than control low fundamental frequency. Finally, trained listeners perceived control loudness as more aberrant than off-season loudness and they noted vocal fry twice as many times in in-season and off-season than in control voices. Conclusions This study exposed traces of adverse voice reactions to coaching and confirmed that coaches harbor a job-based proclivity to voice overuse. Self-reported measures appeared to be the least and aerodynamic the most immune to phonatory exertion that pervades daily coaching tasks. Future studies are warranted to further delineate how athletic coaching interferes with voice production.

Purpose The instrumental assessment of voice quality is influenced by several factors, including the type of recording equipment used to capture the acoustic signal and the algorithm used by the ac...

Purpose Research on language planning in adult stuttering is relatively sparse and offers diverging arguments about a potential causative relationship between semantic and phonological encoding and fluency breakdowns. This study further investigated semantic and phonological encoding efficiency in adults who stutter (AWS) by means of silent category and phoneme identification, respectively. Method Fifteen AWS and 15 age- and sex-matched adults who do not stutter (ANS) participated. The groups were compared on the basis of the accuracy and speed of superordinate category (animal vs. object) and initial phoneme (vowel vs. consonant) decisions, which were indicated manually during silent viewing of pictorial stimuli. Movement execution latency was accounted for, and no other cognitive, linguistic, or motor demands were posed on participants' responses. Therefore, category identification accuracy and speed were considered indirect measures of semantic encoding efficiency and phoneme identification accuracy and speed of phonological encoding efficiency. Results For category decisions, AWS were slower but not less accurate than ANS, with objects eliciting more errors and slower responses than animals in both groups. For phoneme decisions, the groups did not differ in accuracy, with consonant errors outnumbering vowel errors in both groups, and AWS were slower than ANS in consonant but not vowel identification, with consonant response time lagging behind vowel response time in AWS only. Conclusions AWS were less efficient than ANS in semantic encoding, and they might harbor a consonant-specific phonological encoding weakness. Future independent studies are warranted to discover if these positive findings are replicable and a marker for persistent stuttering.

To investigate voice changes as they develop over time due to cigarette smoking, women who never smoked (NS), women who smoked less than 10 years (S1), and women who smoked 10 or more years (S2) were compared. Acoustic (fundamental frequency, jitter, shimmer, signal-to-noise ratio), electroglottographic (open, closing, and speed quotients), aerodynamic (subglottal pressure, airflow, laryngeal airway resistance), and perceptual measures were obtained. Fundamental frequency and open quotient significantly decreased and speed quotient significantly increased in S1 and S2; jitter and shimmer significantly increased in S2 only. NS were perceived as non-smokers more reliably than S1 and S2 as smokers. Fundamental frequency, open quotient, and speed quotient were the most sensitive indicators of smoking effects on the female voice.

The purpose of this study was to compare the speed of phonological encoding between adults who stutter (AWS) and adults who do not stutter (ANS). Fifteen male AWS and 15 age- and gender-matched ANS participated in the study. Speech onset latency was obtained for both groups and stuttering frequency was calculated for AWS during three phonological priming tasks: (1) heterogeneous, during which the participants’ single-word verbal responses differed phonemically; (2) C-homogeneous, during which the participants’ response words shared the initial consonant; and (3) CV-homogeneous, during which the participants’ response words shared the initial consonant and vowel. Response words containing the same C and CV patterns in the two homogeneous conditions served as phonological primes for one another, while the response words in the heterogeneous condition did not. During each task, the participants produced a verbal response after being visually presented with a semantically related cue word, with cue-response pairs being learned beforehand. The data showed that AWS had significantly longer speech onset latency when compared to ANS in all priming conditions, priming had a facilitating effect on word retrieval for both groups, and there was no significant change in stuttering frequency across the conditions for AWS. This suggests that phonological encoding may play no role, or only a minor role, in stuttering. Educational objectives : The reader will be able to: (1) describe previous research paradigms that have been used to assess phonological encoding in adults and children who stutter; (2) explain performance similarities and differences between adults who do and do not stutter during various phonological priming conditions; (3) compare the present findings to past research that examined the relationship between phonological encoding and stuttering.