多媒体系统(MS)期刊详细介绍了多媒体计算,通信,存储和应用的各个方面的创新研究思想,新兴技术,最新方法和工具。它包含理论,实验和调查文章。多媒体系统的覆盖范围包括:在计算机系统中集成数字视频和音频功能;多媒体信息编码和数据交换格式;数字多媒体的操作系统机制;数字视频和音频网络与通信;存储模型和结构;用于支持多媒体应用程序的方法、范式、工具和软件体系结构;多媒体应用程序和应用程序接口,以及多媒体终端系统架构。 官网地址:http://dblp.uni-trier.de/db/journals/mms/

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In a hybrid speech model, both voiced and unvoiced components can coexist in a segment. Often, the voiced speech is regarded as the deterministic component, and the unvoiced speech and additive noise are the stochastic components. Typically, the speech signal is considered stationary within fixed segments of 20-40 ms, but the degree of stationarity varies over time. For decomposing noisy speech into its voiced and unvoiced components, a fixed segmentation may be too crude, and we here propose to adapt the segment length according to the signal local characteristics. The segmentation relies on parameter estimates of a hybrid speech model and the maximum a posteriori (MAP) and log-likelihood criteria as rules for model selection among the possible segment lengths, for voiced and unvoiced speech, respectively. Given the optimal segmentation markers and the estimated statistics, both components are estimated using linear filtering. A codebook-based approach differentiates between unvoiced speech and noise. A better extraction of the components is possible by taking into account the adaptive segmentation, compared to a fixed one. Also, a lower distortion for voiced speech and higher segSNR for both components is possible, as compared to other decomposition methods.

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