ABSTRACT
In this paper, a new calculating method of generalized dimension, based on boxes-coupling principle, is proposed to overcome the edge effects and to improve the capability of the speech endpoint detection which is based on the original calculating method of generalized dimension. This new method has been applied to speech endpoint detection. Firstly, the length of overlapping border was determined, and through calculating the generalized dimension by covering the speech signal with overlapped boxes, three-dimension feature vectors including the box dimension, the information dimension and the correlation dimension were obtained. Secondly, in the light of the relation between feature distance and similarity degree, feature extraction was conducted by use of common distance. Lastly, bi-threshold method was used to classify the speech signals. The results of experiment indicated that, by comparison with the original generalized dimension (OGD) and the spectral entropy (SE) algorithm, the proposed method is more robust and effective for detecting the speech signals which contain different kinds of noise in different signal noise ratio (SNR), especially in low SNR.
Subject(s)
Humans , Artificial Intelligence , Pattern Recognition, Automated , Methods , Signal Processing, Computer-Assisted , Speech , Speech Production Measurement , Methods , Speech Recognition SoftwareABSTRACT
Aim To observe the effect of ZDY102, a C25 stereo-isomer of ZMS, the active component of Zhimu, on brain M receptor density of dementia model animals and the correlation with its effect on learning/memory ability. Methods The rats were randomly divided into five groups: control group, model group, model given orally for 2 months with 3.6 mg?kg -1?d -1 of ZDY102 treatment, model treated with 9.0 mg?kg -1?d -1 of ZDY102, and model treated with 18.0 mg?kg -1?d -1 of ZDY102. Dementia model was produced by single unilateral injection of 4 ?l of normal saline containing 4 ?g of ?-amyloid (25～35) and 1 ?g of ibotenic acid into right basal ganglion region with the aid of a stereotaxic equipment. The brain muscarinic receptor density was analyzed with single-site binding assay using 3H-quinuclidinyl benzilae(QNB). The learning/memory ability was measured by Y-maze performance. Results Two months after model production, the learning and memory ability as well as the density of muscarinic receptor in brain were significantly decreased in model rats compared with those in control rats. Parallel models treated with daily oral administration of ZDY102 for two months improved in learning and memory ability and their muscarinic receptor density was significantly increased when compared with model rats. The correlation coefficient between total M receptor densities and the learning/memory ability was significant when examined with linear regression. Conclusion ZDY102 can significantly improve the learning and memory ability and increase the brain muscarinic receptor density of the model. Since brain muscarinic receptors are closely correlated to learning and memory, up-regulation of M receptor density might play a very important role in the therapeutic effect of ZDY102.