Spectral zero-crossings: Localization properties and application to epoch extraction in speech signals

Abstract

We analyze the spectral zero-crossing rate (SZCR) properties of transient signals and show that SZCR contains accurate localization information about the transient. For a train of pulses containing transient events, the SZCR computed on a sliding window basis is useful in locating the impulse locations accurately. We present the properties of SZCR on standard stylized signal models and then show how it may be used to estimate the epochs in speech signals. We also present comparisons with some state-of-the-art techniques that are based on the group-delay function. Experiments on real speech show that the proposed SZCR technique is better than other group-delaybased epoch detectors. In the presence of noise, a comparison with the zero-frequency filtering technique (ZFF) and Dynamic programming projected Phase-Slope Algorithm (DYPSA) showed that performance of the SZCR technique is better than DYPSA and inferior to that of ZFF. For highpass-filtered speech, where ZFF performance suffers drastically, the identification rates of SZCR are better than those of DYPSA.

ZCR-aided neurocomputing: A study with applications

“…An interesting aspect of ZCRs was shown by the authors of article [21] , who analysed transient signals to demonstrate these can be accurately found based on zero-crossings. Applications related to the estimate of epochs in speech signals were performed, confirming the authors' assumptions.…”

Zero-Crossing Analysis and Information Divergence of Lévy Walks for Real-Time Feature Extraction

“…Many signals are quasistationary, as is the case of speech, and their properties (e.g., level-crossings, zero-crossings, energy, and information theoretic related features) are often studied by segmenting them in windows that are stationary within that specific window (Shenoy & Seelamantula, 2012). Even though speech is a non-stationary signal, it remains nearly unvaried for small segments (i.e., for 10 to 50 ms) (Jalil, Butt, & Malik, 2013).…”