  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.
