组件特定时间分解:应用于增强语音编码和协同发音分析

Tilak Purohit, V. Ramasubramanian
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引用次数: 0

摘要

Atal于1983年提出了一种称为时间分解(temporal decomposition, TD)的语音编码算法,该算法将LPC导出的对数区域参数的时间序列分解为与其相关事件向量对应的重叠事件/插值函数序列。该方法提供了一个与所有区域参数相对应的“全局”事件函数。在这项工作中,我们扩展了Atal的方法来获得对应于每个区域参数的分量级事件函数,并经验表明使用分量级目标函数而不是全局目标函数可以减少信号重构误差。当所提出的方法用于分解发音表示时,该工作可以进一步用于通过推断组件级事件函数来研究对应于单个发音器的协同发音行为。
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Component-specific temporal decomposition: application to enhanced speech coding and co-articulation analysis
Atal in 1983 proposed a speech coding algorithm called temporal decomposition (TD), which decomposes a time sequence of LPC derived log-area parameters, into a sequence of overlapping event/interpolation functions corresponding to their associated event vectors. The method provides a “global” event function corresponding to all the area parameters. In this work, we extend Atal’s methodology to obtain the component level event functions corresponding to each area parameter and empirically show that the signal reconstruction error reduces using the component level target function rather than a global target function. This work can further be used to study the coarticulation behavior corresponding to individual articulators by inferring the component level event functions when the proposed method is used for decomposing the articulatory representations.
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