Voice disorders affect millions of Americans. The impact of voice disorders on quality of life is significant;the ability to work, relate to friendsand family, participate in social activities, and engage in everyday life becomes effortful, if not impossible, when one's voice is impaired. The complexity of voice production and aperiodic nature of voice disorders necessitate that quantitative acoustic analysis be nonlinear. Linear parameters such as jitter or shimmer rely on a linear signal and thus are invalid and inaccurate when applied to aperiodic dysphonia. Current nonlinear methods are only valid for aperiodic signals created primarily by vocal fold vibration (which is inherently of limited order), not signas with prominent turbulent airflow (high order). As turbulent airflow due to breathiness is a common feature of dysphonia, it is important to develop methods of acoustic analysis which are valid for signals with prominent breathy noise. We will apply high-order nonlinear dynamic theory to quantify these signals. We will also perform computer modeling, excised larynx, and human subject experiments to determine the mechanisms by which turbulence is produced. In Project 1, we will optimize high-order nonlinear dynamic parameters capable of analyzing voice signals with prominent turbulent airflow. Traditional descriptions of voice signals use a three class system, with type 1 being periodic, type 2 having subharmonics, and type 3 being aperiodic. It would be beneficial to subdivide type 3 signals into those created predominantly by vocal fold vibration and those created predominantly by turbulent airflow. Current acoustic analyses, whether linear or nonlinear, are not capable of analyzing signals created predominantly by turbulent airflow. High-order nonlinear parameters such as embedding efficiency, generalized dimension, and generalized entropy can quantify these signals. In Projects 2-3, we will perform experiments using computer and excised larynx models to elucidate the mechanisms underlying glottal turbulence. We will also determine the level of abnormality required (e.g., size of polyp or glottal gap) required to produce turbulent energy such that current nonlinear parameters are no longer accurate and high-order nonlinear analysis must be employed. In Projects 4-5, we will evaluate the high-order characteristics of human phonation. Utterance (vowels, fricatives) will be varied to evaluate effects of turbulence created in the vocal tract. We will also determine the effects of volume, phonation type (whisper, chest, falsetto), and recording environment. High-order nonlinear characteristics of disordered voice production will be measured in patients with benign mass lesions, edema, and glottic insufficiency as well as esophageal voice users. Lastly, we will determine the sensitivity, specificity, and reliability of high-order nonlinear parameters compared to linear or current nonlinear parameters. The five projects combine theoretical, basic science, translational, and clinical research to enhance understanding of disordered voice production and provide clinicians with a valid method of performing objective, quantitative acoustic analysis on high-dimensional voice signals.
Voice disorders affect millions of Americans with extensive economic impacts on society and potentially debilitating social impacts on individuals. Acoustic analysis of voice quality must account for the complexity of disordered voice characteristics. Current methods of analysis are very time-consuming and not well-suited for breathy or severely disordered voice. We will apply high-order nonlinear analysis methods that can analyze this type of voice quickly and accurately. Quantitative measurements of acoustic voice quality could lead to improved voice assessment and evidence-based treatment of voice disorders.
|Xue, Chao; Pulvermacher, Allyson; Calawerts, William et al. (2016) An Excised Canine Model of Anterior Glottic Web and Its Acoustic, Aerodynamic, and High-speed Measurements. J Voice :|
|Calawerts, William M; Lin, Liyu; Sprott, J C et al. (2016) Using Rate of Divergence as an Objective Measure to Differentiate between Voice Signal Types Based on the Amount of Disorder in the Signal. J Voice :|
|Lin, Liyu; Calawerts, William; Dodd, Keith et al. (2016) An Objective Parameter for Quantifying the Turbulent Noise Portion of Voice Signals. J Voice 30:664-669|
|Choi, Seong Hee; Zhang, Yu; Jiang, Jack J et al. (2012) Nonlinear dynamic-based analysis of severe dysphonia in patients with vocal fold scar and sulcus vocalis. J Voice 26:566-76|
|Chai, Lingying; Sprecher, Alicia J; Zhang, Yi et al. (2011) Perturbation and nonlinear dynamic analysis of adult male smokers. J Voice 25:342-7|
|Maccallum, Julia K; Zhang, Yu; Jiang, Jack J (2011) Vowel selection and its effects on perturbation and nonlinear dynamic measures. Folia Phoniatr Logop 63:88-97|
|Sprecher, Alicia; Olszewski, Aleksandra; Jiang, Jack J et al. (2010) Updating signal typing in voice: addition of type 4 signals. J Acoust Soc Am 127:3710-16|
|Shao, Jun; MacCallum, Julia K; Zhang, Yu et al. (2010) Acoustic analysis of the tremulous voice: assessing the utility of the correlation dimension and perturbation parameters. J Commun Disord 43:35-44|
|Zhang, Yu; Bieging, Erik; Tsui, Henry et al. (2010) Efficient and effective extraction of vocal fold vibratory patterns from high-speed digital imaging. J Voice 24:21-9|
|Zhu, Yanmei; Witt, Rachel E; MacCallum, Julia K et al. (2010) Effects of the Voice over Internet Protocol on perturbation analysis of normal and pathological phonation. Folia Phoniatr Logop 62:288-96|
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