A novel inverse quantization algorithm based on Taylor series for digital audio codecs

Author(s):  
Fan Liu ◽  
Junfeng Zhu ◽  
Xiaozong Huang ◽  
Xun Xiang
2019 ◽  
Vol 4 (6) ◽  
pp. 1589-1594
Author(s):  
Yvonne van Zaalen ◽  
Isabella Reichel

Purpose Among the best strategies to address inadequate speech monitoring skills and other parameters of communication in people with cluttering (PWC) is the relatively new but very promising auditory–visual feedback (AVF) training ( van Zaalen & Reichel, 2015 ). This study examines the effects of AVF training on articulatory accuracy, pause duration, frequency, and type of disfluencies of PWC, as well as on the emotional and cognitive aspects that may be present in clients with this communication disorder ( Reichel, 2010 ; van Zaalen & Reichel, 2015 ). Methods In this study, 12 male adolescents and adults—6 with phonological and 6 with syntactic cluttering—were provided with weekly AVF training for 12 weeks, with a 3-month follow-up. Data was gathered on baseline (T0), Week 6 (T1), Week 12 (T2), and after follow-up (T3). Spontaneous speech was recorded and analyzed by using digital audio-recording and speech analysis software known as Praat ( Boersma & Weenink, 2017 ). Results The results of this study indicated that PWC demonstrated significant improvements in articulatory rate measurements and in pause duration following the AVF training. In addition, the PWC in the study reported positive effects on their ability to retell a story and to speak in more complete sentences. PWC felt better about formulating their ideas and were more satisfied with their interactions with people around them. Conclusions The AVF training was found to be an effective approach for improving monitoring skills of PWC with both quantitative and qualitative benefits in the behavioral, cognitive, emotional, and social domains of communication.


ASHA Leader ◽  
2008 ◽  
Vol 13 (14) ◽  
pp. 19-19 ◽  
Author(s):  
Greg Snyder ◽  
Peter Reitzes ◽  
Eric Jackson
Keyword(s):  

IEE Review ◽  
1992 ◽  
Vol 38 (4) ◽  
pp. 131 ◽  
Author(s):  
Henry Price

IEE Review ◽  
1992 ◽  
Vol 38 (6) ◽  
pp. 216
Author(s):  
Edward C. Forster

1998 ◽  
Vol 37 (03) ◽  
pp. 235-238 ◽  
Author(s):  
M. El-Taha ◽  
D. E. Clark

AbstractA Logistic-Normal random variable (Y) is obtained from a Normal random variable (X) by the relation Y = (ex)/(1 + ex). In Monte-Carlo analysis of decision trees, Logistic-Normal random variates may be used to model the branching probabilities. In some cases, the probabilities to be modeled may not be independent, and a method for generating correlated Logistic-Normal random variates would be useful. A technique for generating correlated Normal random variates has been previously described. Using Taylor Series approximations and the algebraic definitions of variance and covariance, we describe methods for estimating the means, variances, and covariances of Normal random variates which, after translation using the above formula, will result in Logistic-Normal random variates having approximately the desired means, variances, and covariances. Multiple simulations of the method using the Mathematica computer algebra system show satisfactory agreement with the theoretical results.


2005 ◽  
Vol 10 (4) ◽  
pp. 333-342
Author(s):  
V. Chadyšas ◽  
D. Krapavickaitė

Estimator of finite population parameter – ratio of totals of two variables – is investigated by modelling in the case of simple random sampling. Traditional estimator of the ratio is compared with the calibrated estimator of the ratio introduced by Plikusas [1]. The Taylor series expansion of the estimators are used for the expressions of approximate biases and approximate variances [2]. Some estimator of bias is introduced in this paper. Using data of artificial population the accuracy of two estimators of the ratio is compared by modelling. Dependence of the estimates of mean square error of the estimators of the ratio on the correlation coefficient of variables which are used in the numerator and denominator, is also shown in the modelling.


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