论文标题
自动语音极性检测的残余激发偏度
Residual Excitation Skewness for Automatic Speech Polarity Detection
论文作者
论文摘要
在几种语音处理技术之前，检测正确的语音极性是必要的步骤。确定其确定的错误可能会对其性能产生巨大的有害影响。由于当前系统必须处理来自多个设备的越来越多的数据，因此语音极性的自动检测已成为一个关键问题。为此，我们在这里提出了一种基于两个激发信号的偏度的非常简单的算法。该方法显示在10个语音语料库（8545个文件）上，在清洁条件下仅导致0.06％的错误率，并且明显超过了四种最新方法。此外，它通过简单性大大减少了计算负载，并且可以观察到在嘈杂和混响环境中表现出最强的鲁棒性。
Detecting the correct speech polarity is a necessary step prior to several speech processing techniques. An error on its determination could have a dramatic detrimental impact on their performance. As current systems have to deal with increasing amounts of data stemming from multiple devices, the automatic detection of speech polarity has become a crucial problem. For this purpose, we here propose a very simple algorithm based on the skewness of two excitation signals. The method is shown on 10 speech corpora (8545 files) to lead to an error rate of only 0.06% in clean conditions and to clearly outperform four state-of-the-art methods. Besides it significantly reduces the computational load through its simplicity and is observed to exhibit the strongest robustness in both noisy and reverberant environments.
