Speech Enhancement With Inventory Style Speech Resynthesis

We present a new method for the enhancement of speech. The method is designed for scenarios in which targeted speaker enrollment as well as system training within the typical noise environment are feasible. The proposed procedure is fundamentally different from most conventional and state-of-the-art denoising approaches. Instead of filtering a distorted signal we are resynthesizing a new “clean” signal based on its likely characteristics. These characteristics are estimated from the distorted signal. A successful implementation of the proposed method is presented. Experiments were performed in a scenario with roughly one hour of clean speech training data. Our results show that the proposed method compares very favorably to other state-of-the-art systems in both objective and subjective speech quality assessments. Potential applications for the proposed method include jet cockpit communication systems and offline methods for the restoration of audio recordings.

Development of the Heat and Energy Concept Inventory: Preliminary Results on the Prevalence and Persistence of Engineering Students' Misconceptions

BACKGROUND Students frequently hold a number of misconceptions related to temperature, heat and energy. There is not currently a concept inventory with sufficiently high internal reliability to assess these concept areas for research purposes. Consequently, there is little data on the prevalence of these misconceptions amongst undergraduate engineering students. PURPOSE (HYPOTHESIS) This work presents the Heat and Energy Concept Inventory (HECI) to assess prevalent misconceptions related to: (1) Temperature vs. Energy, (2) Temperature vs. Perceptions of Hot and Cold, (3) Factors that affect the Rate vs. Amount of Heat Transfer and (4) Thermal Radiation. The HECI is also used to document the prevalence of misconceptions amongst undergraduate engineering students. DESIGN/METHOD Item analysis, guided by classical test theory, was used to refine individual questions on the HECI. The HECI was used in a one group, pre-test-post-test design to assess the prevalence and persistence of targeted misconceptions amongst a population of undergraduate engineering students at diverse institutions. RESULTS Internal consistency reliability was assessed using Kuder-Richardson Formula 20; values were 0.85 for the entire instrument and ranged from 0.59 to 0.76 for the four subcategories of the HECI. Student performance on the HECI went from 49.2% to 54.5% after instruction. Gains on each of the individual subscales of the HECI, while generally statistically significant, were similarly modest. CONCLUSIONS The HECI provides sufficiently high estimates of internal consistency reliability to be used as a research tool to assess students' understanding of the targeted concepts. Use of the instrument demonstrates that student misconceptions are both prevalent and resistant to change through standard instruction.

Corpus-Based Speech Enhancement With Uncertainty Modeling and Cepstral Smoothing

We present a new approach for corpus-based speech enhancement that significantly improves over a method published by Xiao and Nickel in 2010. Corpus-based enhancement systems do not merely filter an incoming noisy signal, but resynthesize its speech content via an inventory of pre-recorded clean signals. The goal of the procedure is to perceptually improve the sound of speech signals in background noise. The proposed new method modifies Xiao's method in four significant ways. Firstly, it employs a Gaussian mixture model (GMM) instead of a vector quantizer in the phoneme recognition front-end. Secondly, the state decoding of the recognition stage is supported with an uncertainty modeling technique. With the GMM and the uncertainty modeling it is possible to eliminate the need for noise dependent system training. Thirdly, the post-processing of the original method via sinusoidal modeling is replaced with a powerful cepstral smoothing operation. And lastly, due to the improvements of these modifications, it is possible to extend the operational bandwidth of the procedure from 4 kHz to 8 kHz. The performance of the proposed method was evaluated across different noise types and different signal-to-noise ratios. The new method was able to significantly outperform traditional methods, including the one by Xiao and Nickel, in terms of PESQ scores and other objective quality measures. Results of subjective CMOS tests over a smaller set of test samples support our claims.

The Behavior Rating Inventory Of Executive Function - Self-Report Version (Brief-Sr) And The Delis-Kaplan Executive Function Sys

The assessment of executive functions is an area of study that has seen considerable development in recent years. Despite much research examining the validity of various measures of executive functions from both a direct and indirect format, little evidence exists in the extant literature evaluating the correspondence between these types of measures. The current study examined the extent of correspondence, comprising concurrent validity, between the Delis-Kaplan Executive Function System (D-KEFS) and the Behavior Rating Inventory of Executive Function ¿ Self-Report Version (BRIEF-SR). Participants included 30 undergraduate and high school students 18 years of age. Results indicated mixed evidence of concurrent validity between the two measures of executive functions. The findings obtained suggest both expected significant, negative correlation as well as lack of expected correlation between the measures. Suggestions for future research in the assessment of executive functions are discussed.