Download Advances in Non-Linear Modeling for Speech Processing by Raghunath S. Holambe PDF

By Raghunath S. Holambe

Advances in Non-Linear Modeling for Speech Processing comprises complex subject matters in non-linear estimation and modeling suggestions in addition to their purposes to speaker reputation.

Non-linear aeroacoustic modeling method is used to estimate the real fine-structure speech occasions, which aren't printed by way of the quick time Fourier remodel (STFT). This aeroacostic modeling technique offers the impetus for the excessive answer Teager power operator (TEO). This operator is characterised by means of a time solution which may music fast sign strength adjustments inside of a glottal cycle.

The cepstral beneficial properties like linear prediction cepstral coefficients (LPCC) and mel frequency cepstral coefficients (MFCC) are computed from the importance spectrum of the speech body and the part spectra is missed. to beat the matter of neglecting the part spectra, the speech creation method may be represented as an amplitude modulation-frequency modulation (AM-FM) version. To demodulate the speech sign, to estimation the amplitude envelope and immediate frequency parts, the power separation set of rules (ESA) and the Hilbert remodel demodulation (HTD) set of rules are mentioned.

Different good points derived utilizing above non-linear modeling strategies are used to boost a speaker id method. ultimately, it truly is proven that, the fusion of speech construction and speech belief mechanisms may end up in a powerful characteristic set.

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In: Proceedings of second IEEE international conference on emerging trends in engineering and technology (ICETET’09), Nagpur, pp 880–884 19. Deshpande MS, Holambe RS (2009) Robust q features for speaker identification. In: Proceedings of IEEE international conference on advances in recent technologies in communication and computing (ARTCom’09), Kottayam, Kerala, pp 209–213 20. Honda K (2008) Physiological processes of speech production. Springer, Berlin 21. Kitamura T, Honda K, Takemoto H (2005) Individual variation of the hypopharyngeal cavities and its acoustic effects.

1 Linear Speech Production Model A general discrete-time linear speech production model, shown in Fig. 1, describes the voiced and unvoiced modes of speech separately. Where s(n) is the sampled speech waveform, n is the sample number, u L (n) is the volume velocity signal at the lips, u G (n) is the glottal signal (which is the input into the vocal tract), V (z) is the vocal tract transfer function and R(z) is the lip radiation transfer function. The system is assumed to be time-invariant over a time period of about 10–30 ms [10].

3 The Linear Source-Filter Model The linear modeling of the speech production was motivated by the lossless tube model of the vocal tract [5]. Fant conducted a study on speech intelligibility [6] and Miller estimated the voice source signal by using the inverse of the first vocal resonance and the vocal fold opening area measured by video [7]. A linear sourcetract model was proposed to represent the radiation impedance, vocal tract and the glottal source as linear filters and identified using covariance analysis [8, 9].

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