# Residual Excitation Skewness for Automatic Speech Polarity Detection

arXiv: https://arxiv.org/abs/2006.00525 · HTML: https://mlsanity.com/paper/2006.00525/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 31 May 2020.

## Built on by (most cited first, 1 of 1)

- [Neural Speech Synthesis on a Shoestring: Improving the Efficiency of LPCNet](https://mlsanity.com/paper/2202.11169/) (2022)

## Abstract (arXiv)

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.