Vocal hyperfunction (VH), which is characterized by excessive laryngeal tension, accounts for nearly half of the cases referred to multidisciplinary voice clinics and. It can respond to behavioral intervention, but successful treatment depends on proper assessment. Current assessment is hampered by the lack of objective measures for detecting its presence or severity. Relative Fundamental Frequency (RFF, the change in fundamental frequency in vowels preceding and following unvoiced consonants, normalized by fundamental frequency in the more steady state portions vowels) can objectively characterize VH. However, RFF estimates are currently performed manually by trained technicians and clinicians from running speech such that the potential of RFF in diagnosis and assessment is limited by the time-consuming manual nature of RFF estimation. This study will determine the optimal speech stimuli and signal processing for development of automated RFF estimation. We will determine the differences in RFF estimates from running speech versus non-linguistic speech utterances, the effect of linguistic context on the relationship between RFF and vocal tension, and the impact of dysphonia severity on the automated RFF measure. Vocal tension will be estimated in healthy and disordered voices using listener perception of vocal strain, and cross-validated in healthy speakers using objective measurements of the ratio of sound pressure level to subglottal pressure (dB SPL / cm H2O). Measures of RFF estimated using non-linguistic speech utterances have the potential to be automated more reliably. Based on our empirical research, we will develop recommendations for clinical methods of RFF collection to optimize automatic RFF estimation: full running or non-linguistic speech. We will further develop open source algorithms and software for automated RFF estimation. Automated RFF estimation would enable comprehensive clinical collection, facilitating future validation of this promising measure.
For the 3-9% of the U.S. population with a voice disorder, communication is impaired, causing them to suffer both economically and socially. Vocal hyperfunction is characterized by excessive laryngeal and paralaryngeal tension and accounts for nearly half of cases referred to multidisciplinary voice clinics. This project will validate an automated measure of vocal hyperfunction to improve assessment and treatment.
|Murray, Elizabeth S Heller; Hands, Gabrielle L; Calabrese, Carolyn R et al. (2016) Effects of Adventitious Acute Vocal Trauma: Relative Fundamental Frequency and Listener Perception. J Voice 30:177-85|
|Lien, Yu-An S; Calabrese, Carolyn R; Michener, Carolyn M et al. (2015) Voice Relative Fundamental Frequency Via Neck-Skin Acceleration in Individuals With Voice Disorders. J Speech Lang Hear Res 58:1482-7|
|Lien, Yu-An S; Michener, Carolyn M; Eadie, Tanya L et al. (2015) Individual Monitoring of Vocal Effort With Relative Fundamental Frequency: Relationships With Aerodynamics and Listener Perception. J Speech Lang Hear Res 58:566-75|
|Cler, Meredith J; Stepp, Cara E (2015) Discrete Versus Continuous Mapping of Facial Electromyography for Human-Machine Interface Control: Performance and Training Effects. IEEE Trans Neural Syst Rehabil Eng 23:572-80|
|Anand, Supraja; Stepp, Cara E (2015) Listener Perception of Monopitch, Naturalness, and Intelligibility for Speakers With Parkinson's Disease. J Speech Lang Hear Res 58:1134-44|
|Varghese, Lenny A; Mendoza, Joseph O; Braden, Maia N et al. (2014) Effects of spectral content on Horii Oral-Nasal Coupling scores in children. J Acoust Soc Am 136:1295|
|Lien, Yu-An S; Gattuccio, Caitlin I; Stepp, Cara E (2014) Effects of phonetic context on relative fundamental frequency. J Speech Lang Hear Res 57:1259-67|
|Cler, Meredith J; Michener, Carolyn M; Stepp, Cara E (2014) Discrete vs. continuous surface electromyographic interface control. Conf Proc IEEE Eng Med Biol Soc 2014:4374-7|
|Cler, Meredith J; Nieto-Castanon, Alfonso; Guenther, Frank H et al. (2014) Surface electromyographic control of speech synthesis. Conf Proc IEEE Eng Med Biol Soc 2014:5848-51|
|Hands, Gabrielle L; Larson, Eric; Stepp, Cara E (2014) Effects of augmentative visual training on audio-motor mapping. Hum Mov Sci 35:145-55|
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