Automatic prosodic break detection and annotation are important for both speech understanding and natural speech synthesis. In this paper, we discuss automatic prosodic break detection and feature analysis. The contri...Automatic prosodic break detection and annotation are important for both speech understanding and natural speech synthesis. In this paper, we discuss automatic prosodic break detection and feature analysis. The contributions of the paper are two aspects. One is that we use classifier combination method to detect Mandarin and English prosodic break using acoustic, lexical and syntactic evidence. Our proposed method achieves better performance on both the Mandarin prosodic annotation corpus Annotated Speech Corpus of Chinese Discourse and the English prosodic annotation corpus -- Boston University Radio News Corpus when compared with the baseline system and other researches＇ experimental results. The other is the feature analysis for prosodic break detection. The functions of different features, such as duration, pitch, energy, and intensity, are analyzed and compared in Mandarin and English prosodic break detection. Based on the feature analysis, we also verify some linguistic conclusions.展开更多
In this paper we aim to analyse temporal variation of CD4 cell counts for HIV-infected individuals under antiretroviral therapy by using statistical methods. This is achieved by resorting to recursive binary regressio...In this paper we aim to analyse temporal variation of CD4 cell counts for HIV-infected individuals under antiretroviral therapy by using statistical methods. This is achieved by resorting to recursive binary regression tree approach [1]?[2]. This approach has made it possible to highlight the existence of several segments of the population of interest described by the interactions between the predictive covariates of the response to the treatment regimen.展开更多
交通拥堵检测是城市交通管理工作的重点和难点之一,现有的拥堵检测以路段为单位,不利于拥堵时空演变规律信息的提取,且检测内容大多只涉及拥堵程度,缺少对拥堵类型的识别。基于CART(classification and regression tree)分类树算法,提...交通拥堵检测是城市交通管理工作的重点和难点之一,现有的拥堵检测以路段为单位,不利于拥堵时空演变规律信息的提取,且检测内容大多只涉及拥堵程度,缺少对拥堵类型的识别。基于CART(classification and regression tree)分类树算法,提出一种以路段点为检测单元的拥堵点分类检测方法,该方法可根据路段平均行驶速度实时检测拥堵点及其类型。首先,将路段等距离划分后映射为路段点,根据时空维路况异常规则和异常模式,以路段点为单元分析了4种拥堵类型的时空演变模式;其次,在路段路况检测的基础上,提取路段点路况时空序列,根据不同类型的拥堵模式对路况时空序列进行分类标记;然后,选取4种速度指标作为样本属性集合,按照属性集合提取各路段点在各时段的速度,以此作为决策树学习的数据集;最后,基于CART分类树算法,采用交叉验证的方式训练出最优模型,使其达到最佳的泛化能力。与支持向量机(support vector machine,SVM)分类模型进行比较,实验结果表明,该方法在分类检测交通拥堵点时具有较高的正确率和召回率,且分类检测时效性较好。展开更多
基金Supported by the National Natural Science Foundation of China under Grant Nos. 90820303,90820011the Natural Science Foundation of Shandong Province of China under Grant No. ZR2011FQ024
文摘Automatic prosodic break detection and annotation are important for both speech understanding and natural speech synthesis. In this paper, we discuss automatic prosodic break detection and feature analysis. The contributions of the paper are two aspects. One is that we use classifier combination method to detect Mandarin and English prosodic break using acoustic, lexical and syntactic evidence. Our proposed method achieves better performance on both the Mandarin prosodic annotation corpus Annotated Speech Corpus of Chinese Discourse and the English prosodic annotation corpus -- Boston University Radio News Corpus when compared with the baseline system and other researches＇ experimental results. The other is the feature analysis for prosodic break detection. The functions of different features, such as duration, pitch, energy, and intensity, are analyzed and compared in Mandarin and English prosodic break detection. Based on the feature analysis, we also verify some linguistic conclusions.
文摘In this paper we aim to analyse temporal variation of CD4 cell counts for HIV-infected individuals under antiretroviral therapy by using statistical methods. This is achieved by resorting to recursive binary regression tree approach [1]?[2]. This approach has made it possible to highlight the existence of several segments of the population of interest described by the interactions between the predictive covariates of the response to the treatment regimen.
