Abstract
Epoch extraction helps in speech enhancement and multispeaker separation from a speech. But it is a challenging task due to time-varying characteristics of the source and the system. Epoch sequence is useful to manipulate prosody in speech synthesis applications. Accurate estimation of epochs helps in characterizing voice quality features. This chapter aims at developing an extraction algorithm independent of the characteristics of vocal tract system. It improves the accuracy of epochs extracted and pitch detected from speech signal. For feature detection, we propose a robust framework derived from Hilbert–Huang transform of speech signal. The intrinsic mode functions (IMF) sharply identify instantaneous frequencies as function of time. The proposed technique guarantees accurate pitch estimation because of better decorrelating nature of HHT compared with DCT and DFTs. The results are simulated for an input speech signal taken from NOISEX-92 database. The simulated results show that the proposed algorithm outperforms the existing methods.
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Samiappan, D., Jaba Deva Krupa, A., Monika, R. (2018). Epoch Extraction Using Hilbert–Huang Transform for Identification of Closed Glottis Interval. In: Saini, H., Singh, R., Reddy, K. (eds) Innovations in Electronics and Communication Engineering . Lecture Notes in Networks and Systems, vol 7. Springer, Singapore. https://doi.org/10.1007/978-981-10-3812-9_15
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DOI: https://doi.org/10.1007/978-981-10-3812-9_15
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