A fully automated Vowel Space Area (VSA) computation method is proposed that can be applied to any type of speech. It is shown that the VSA provides an efficient and reliable measure and is correlated to speech intelligibility. A clinical tool that incorporates the automated VSA was proposed for evaluation and treatment to be used by speech language pathologists. Two exploratory studies are performed using two databases by analyzing mean formant trajectories in healthy speech for a wide range of speakers, dialects, and coarticulation contexts. It is shown that phonemes crowded in formant space can often have distinct trajectories, possibly due to accurate perception.
A theory for analyzing time-varying signals models with amplitude modulation and frequency modulation is developed. Examples are provided that demonstrate other possible signal model decompositions with independent basis functions and corresponding physical interpretations. The Hilbert transform (HT) and the use of the analytic form of a signal are motivated, and a proof is provided to show that a signal can still preserve desirable mathematical properties without the use of the HT. A visualization of the Hilbert spectrum is proposed to aid in the interpretation. A signal demodulation is proposed and used to develop a modified Empirical Mode Decomposition (EMD) algorithm.
The present study examined the effects that mild traumatic brain injury (mTBI) has on an individual’s episodic memory by looking at participants’ abilities to recall stories both immediately after being verbally told and after a delay. Thirty-seven participants were sorted into a control group (N=27) and a mTBI group (N=10) and then given the Wechsler Memory Scale’s two subtests, Logical Memory I and Logical Memory II. Logical Memory I consists of two verbally given stories in which the participant immediately retells the story to the assessor with as much detail and original vocabulary as they can remember. Logical Memory II has the participants, without prior knowledge, retell the same two stories after a thirty-minute delay. Once recorded, researchers transcribed and scored the participants’ story recalls, gathering data on what errors, correct ideas, and vocabulary the participants made and remembered. The data was then analyzed through an Analysis of Variance (ANOVA), looking at the interaction of Story (of the two stories that the participants were told), Group (whether mTBI or control) , and Delay (whether it was the immediate or delayed recall). Trends in the data show that participants with a history of mTBI do more poorly than the control group proving that memory is affected by acquired brain injury and that further studies to examine how and why this is the case are needed.