论文标题
振荡语音极性检测的统计矩
Oscillating Statistical Moments for Speech Polarity Detection
论文作者
论文摘要
语音极性的反转可能会对各种语音处理技术的性能产生巨大的有害影响。因此，必须作为确定语音极性（取决于记录设置的）的一种自动方法，作为确保这种技术的良好行为的初步步骤。本文提出了一种依靠振荡统计矩的新的极性检测方法。这些时刻具有在局部基本频率下振荡的特性，并表现出取决于语音极性的相移。这种依赖性源于在计算中引入非线性或高阶统计。与最先进的技术相比，在10个语音语料库中显示了所得的方法，可提供实质性改进。
An inversion of the speech polarity may have a dramatic detrimental effect on the performance of various techniques of speech processing. An automatic method for determining the speech polarity (which is dependent upon the recording setup) is thus required as a preliminary step for ensuring the well-behaviour of such techniques. This paper proposes a new approach of polarity detection relying on oscillating statistical moments. These moments have the property to oscillate at the local fundamental frequency and to exhibit a phase shift which depends on the speech polarity. This dependency stems from the introduction of non-linearity or higher-order statistics in the moment calculation. The resulting method is shown on 10 speech corpora to provide a substantial improvement compared to state-of-the-art techniques.
