Abstract
Empirical mode decomposition (EMD) is a method for nonstationary signal analysis, where signals are decomposed into number of high-frequency modes called intrinsic mode function (IMF)s and a low-frequency component called the residual. If this residual is considered as the source signal in case of a speech signal and vocal tract filter response is estimated, the original signal can be reconstructed. The nonstationary attribute of a speech signal restricts direct application of the conventional digital signal processing (DSP) techniques to a speech signal. Since EMD performs decomposition assuming the nonstationary nature of a signal, it has been observed that frame-by-frame analysis is not required in the proposed reconstruction model. The effectiveness of reconstruction using EMD residual is experimented in case of speech data collected in various conditions like clean, noisy, mobile channel including speaker’s mood variation.
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Goswami, N., Sarma, M., Sarma, K.K. (2015). Effective Speech Signal Reconstruction Technique Using Empirical Mode Decomposition Under Various Conditions. In: Sarma, K., Sarma, M., Sarma, M. (eds) Recent Trends in Intelligent and Emerging Systems. Signals and Communication Technology. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2407-5_12
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DOI: https://doi.org/10.1007/978-81-322-2407-5_12
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