Abstract
Co-channel speech is a combination of speech utterances over a single communication channel. Traditional approach to co-channel speech processing is to attempt to extract the speech of the speaker of interest (target speech) from other (interfering) speech. Usable speech criteria are proposed to extract minimally corrupted speech for speaker identification in co-channel speech. In this paper, we present usable speech extraction method based on pitch information obtained from linear multi-scale decomposition by dyadic wavelet transform and nonlinear multi-scale decomposition by empirical mode decomposition. Detected usable speech are organized into speaker stream, and applied to speaker identification system. The proposed methods are evaluated and compared across various Target to Interferer Ratio (TIR) for speaker identification system.
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Ghezaiel, W., Ben Slimane, A., Ben Braiek, E. (2016). Linear Versus Nonlinear Multi-scale Decomposition for Co-channel Speaker Identification System. In: Esposito, A., et al. Recent Advances in Nonlinear Speech Processing. Smart Innovation, Systems and Technologies, vol 48. Springer, Cham. https://doi.org/10.1007/978-3-319-28109-4_17
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DOI: https://doi.org/10.1007/978-3-319-28109-4_17
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