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

By Raghunath S. Holambe

ISBN-10: 1461415047

ISBN-13: 9781461415046

ISBN-10: 1461415055

ISBN-13: 9781461415053

Advances in Non-Linear Modeling for Speech Processing contains complex themes in non-linear estimation and modeling innovations in addition to their functions to speaker popularity.

Non-linear aeroacoustic modeling process is used to estimate the real fine-structure speech occasions, which aren't printed through the fast time Fourier rework (STFT). This aeroacostic modeling method presents the impetus for the excessive answer Teager strength operator (TEO). This operator is characterised by means of a time answer that could music quick sign strength adjustments inside a glottal cycle.

The cepstral positive factors like linear prediction cepstral coefficients (LPCC) and mel frequency cepstral coefficients (MFCC) are computed from the value spectrum of the speech body and the section spectra is ignored. to beat the matter of neglecting the part spectra, the speech construction method should be represented as an amplitude modulation-frequency modulation (AM-FM) version. To demodulate the speech sign, to estimation the amplitude envelope and prompt frequency elements, the power separation set of rules (ESA) and the Hilbert rework demodulation (HTD) set of rules are mentioned.

Different gains derived utilizing above non-linear modeling ideas are used to boost a speaker identity procedure. eventually, it truly is proven that, the fusion of speech construction and speech notion mechanisms can result in a powerful characteristic set.

Show description

Read Online or Download Advances in Non-Linear Modeling for Speech Processing PDF

Best artificial intelligence books

Download PDF by Gökhan H. Bakir, Thomas Hofmann, Bernhard Schölkopf,: Predicting Structured Data (Neural Information Processing)

Computer studying develops clever computers which are in a position to generalize from formerly visible examples. a brand new area of laptop studying, within which the prediction needs to fulfill the extra constraints present in dependent facts, poses one in every of computing device learning’s maximum demanding situations: studying useful dependencies among arbitrary enter and output domain names.

Christopher M. Bishop's Neural Networks for Pattern Recognition PDF

This is often the 1st finished remedy of feed-forward neural networks from the viewpoint of statistical development popularity. After introducing the fundamental suggestions, the booklet examines recommendations for modeling chance density features and the houses and benefits of the multi-layer perceptron and radial foundation functionality community types.

New PDF release: The Emperor's New Mind Concerning Computers, Minds and the

For many years, proponents of man-made intelligence have argued that pcs will quickly be doing every little thing human brain can do. Admittedly, desktops now play chess on the grandmaster point, yet do they comprehend the sport as we do? Can a working laptop or computer ultimately do every little thing a human brain can do?
In this soaking up and often contentious e-book, Roger Penrose--eminent physicist and winner, with Stephen Hawking, of the celebrated Wolf prize--puts ahead his view that there are a few aspects of human pondering which may by no means be emulated via a desktop. Penrose examines what physics and arithmetic can let us know approximately how the brain works, what they can't, and what we have to comprehend to appreciate the actual approaches of consciousness.
He is between increasingly more physicists who imagine Einstein wasn't being obdurate while he stated his "little finger" informed him that quantum mechanics is incomplete, and he concludes that legislation even deeper than quantum mechanics are crucial for the operation of a brain. To help this rivalry, Penrose takes the reader on a blinding travel that covers such issues as advanced numbers, Turing machines, complexity thought, quantum mechanics, formal structures, Godel undecidability, part areas, Hilbert areas, black holes, white holes, Hawking radiation, entropy, quasicrystals, the constitution of the mind, and rankings of alternative subjects.
The Emperor's New brain will attract an individual with a significant curiosity in smooth physics and its relation to philosophical concerns, in addition to to physicists, mathematicians, philosophers and people on each side of the AI debate.

In the readition of the bestselling Chaos and a short heritage of Time, here's a technological know-how e-book with mainstream attraction. Proponents of man-made intelligence hold that finally a working laptop or computer might be in a position to do every little thing a human brain can do, yet Oxford college Professor of arithmetic Roger Penrose explains his view that there are elements of human pondering that could by no means be emulated by means of a laptop. Drawings all through.

Knowledge Discovery from Legal Databases - download pdf or read online

Wisdom Discovery from criminal Databases is the 1st textual content to explain info mining ideas as they observe to legislation. legislations scholars, felony lecturers and utilized info know-how experts are guided thorough all stages of the information discovery from databases method with transparent causes of diverse facts mining algorithms together with rule induction, neural networks and organization ideas.

Extra info for Advances in Non-Linear Modeling for Speech Processing

Sample text

13) which is the product of squared amplitude and frequency. 2 Exponential Signal The exponentially decaying signal is modeled as x(t) = e−αt . Its Teager energy obtained using Eq. 14) Thus, the exponentially decaying signal has zero Teager energy. 3 AM Signal AM signal modeling is described in Sect. 1. 15) We can see that the Teager energy of an AM signal is composed by a term similar to the energy of a sinusoidal signal, and an oscillation scaled by the Teager Energy of the amplitude signal. 1 shows a sample AM signal (a) and its Teager energy (b).

Ex p − (x − c j )T ⎩ 2 −1 j ⎫⎡ ⎤ ⎬ −1 (x − c j ) ⎣ (x − c j )⎦ , ⎭ j for 1 ≤ i ≤ I, 1 ≤ l ≤ L . 41) If the kernel function of Eq. (αl +1)( x 2 +α 2 )−α−1 xl for 1 ≤ i ≤ I, 1 ≤ l ≤ L . 4 Quasi-Linear Approximation The linear Taylor series approximation discussed above requires evaluation of the Jacobian matrix in an analytical form. If such a form is not available, or some or all elements of the Jacobian matrix do not exist as in the case where discontinuity exists, then a linear approximation to a nonlinear function can be accomplished by the quasi-linear approximation method, which we discuss now.

World Scientific, Singapore, pp 277–330 13. Teager HM, Teager SM (1989) Evidence for nonlinear sound production mechanisms in the vocal tract. In: Hardcastle W, Marchal A (eds) Speech production and speech modeling, vol 55. NATO Advanced Study Institute Series D, Bonas, France 14. Maragos P, Kaiser JF, Quatieri TF (1993) Energy separation in signal modulations with application to speech analysis. IEEE Trans Signal Process 41(10):3024–3051 15. Maragos P, Potamianos A (1999) Fractal dimensions of speech sounds: computation and application to automatic speech recogntion.

Download PDF sample

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

by Ronald

Rated 4.40 of 5 – based on 26 votes