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Speech segmentation is an essential stage in designing automatic speech recognition systems and one can find several algorithms proposed in the literature. It is a difficult problem, as speech is immensely variable. The aim of the authors' studies was to design an algorithm that could be employed at the stage of automatic speech recognition. This would make it possible to avoid some problems related to speech signal parametrization. Posing the problem in such a way requires the algorithm to be capable of working in real time. The only such algorithm was proposed by Tyagi et al., (2006), and it is a modified version of Brandt's algorithm. The article presents a new algorithm for unsupervised automatic speech signal segmentation. It performs segmentation without access to information about the phonetic content of the utterances, relying exclusively on second-order statistics of a speech signal. The starting point for the proposed method is time-varying Schur coefficients of an innovation adaptive filter. The Schur algorithm is known to be fast, precise, stable and capable of rapidly tracking changes in second order signal statistics. A transfer from one phoneme to another in the speech signal always indicates a change in signal statistics caused by vocal track changes. In order to allow for the properties of human hearing, detection of inter-phoneme boundaries is performed based on statistics defined on the mel spectrum determined from the reflection coefficients. The paper presents the structure of the algorithm, defines its properties, lists parameter values, describes detection efficiency results, and compares them with those for another algorithm. The obtained segmentation results, are satisfactory.

This paper presents least squares (LS) and total least squares (TLS) method solutions to compensate mutual coupling effects in a small linear antenna array operating over a narrow frequency band. The validity of the two methods is verified by experimental results performed on a six‐element microstrip patch array operating in the 2.4‐GHz band. The obtained results prove the validity of the two methods and show the superiority of the TLS method over the LS method. © 2004 Wiley Periodicals, Inc. Microwave Opt Technol Lett 40: 391–396, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.11390

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