Hierarchical Neural Network Structures for Phoneme Recognition (Signals and Communication Technology)

By Daniel Vasquez

The topic of this examine is the position of hierarchical constructions, in line with neural networks, in picking phonemes in automatic speech reputation platforms. It indicates how the bogus neural community paradigm can simplify the research of spoken language.

Show description

Quick preview of Hierarchical Neural Network Structures for Phoneme Recognition (Signals and Communication Technology) PDF

Best Engineering books

Fundamentals of Aerodynamics, 5th Edition

In accordance with its bestselling past variants, basics of Aerodynamics, 5th version by means of John Anderson, deals the main readable, attention-grabbing, and up to date evaluate of aerodynamics to be present in any textual content. The vintage association of the textual content has been preserved, as is its winning pedagogical good points: bankruptcy roadmaps, preview containers, layout bins and precis part.

Electrical and Electronic Principles and Technology (3rd Edition)

During this ebook John chook introduces electric ideas and expertise via examples instead of concept - permitting scholars to advance a valid realizing of the rules wanted through technicians in fields comparable to electric engineering, electronics and telecommunications. No prior history in engineering is believed, making this an incredible textual content for vocational classes at point 2 and three, starting place measure and introductory classes for undergraduates.

Engineering Mechanics: Dynamics (13th Edition)

In his revision of Engineering Mechanics, R. C. Hibbeler empowers scholars to reach the complete studying adventure. Hibbeler achieves this by means of calling on his daily school room event and his wisdom of the way scholars study inside and out of lecture. this article is perfect for civil and mechanical engineering execs.

Modern Semiconductor Devices for Integrated Circuits

Smooth Semiconductor units for built-in Circuits, First version introduces readers to the area of recent semiconductor units with an emphasis on built-in circuit purposes. KEY subject matters: Electrons and Holes in Semiconductors; movement and Recombination of Electrons and Holes; equipment Fabrication know-how; PN and Metal–Semiconductor Junctions; MOS Capacitor; MOS Transistor; MOSFETs in ICs—Scaling, Leakage, and different issues; Bipolar Transistor.

Additional info for Hierarchical Neural Network Structures for Phoneme Recognition (Signals and Communication Technology)

Show sample text content

6. 2. 2 Phoneme conversation procedure . . . . . . . . . . . . . . . . . . 6. three precis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 104 106 106 107 108 108 a hundred and ten 111 112 112 113 116 7 precis and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 7. 1 Contributions of This publication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . a hundred and twenty 7. 2 destiny instructions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 thesaurus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131 Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 List of Tables three. 1 TIMIT phoneme set utilized in this ebook. The desk exhibits 39 phonemes including their corresponding articulatory attributes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . forty eight four. 1 Phoneme attractiveness accuracies for different context modeling degrees. The MLPs estimate phoneme posteriors or nation posteriors for 1-state or 3-state modeling respectively. . . . . . . . . MLP functionality given in variety of processed frames consistent with moment. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . functionality of downsampling schemes measured in general frames/utterance on the enter of M LP 2 and computational time of the total hierarchical scheme. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Phoneme accuracies of downsampling schemes. The MLPs estimate phoneme posteriors (1-state) or country posteriors (3-state). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Phoneme reputation accuracies for the hierarchical downsampling method. a number of sampling premiums were established giving M posterior vectors on the enter of M LP 2 masking a temporal context of 2d2 + 1 frames. . . . . . . . . . . . . . . Phoneme attractiveness accuracies for the window downsampling technique. aid of variety of hidden devices of M LP 2 whilst Tw = five and M = five. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Phoneme accuracies of the temporal and window downsampling blend. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . four. 2 four. three four. four four. five four. 6 four. 7 five. 1 fifty four fifty five fifty five fifty six fifty seven fifty seven fifty eight FA of the MLPs located on the first hierarchical point. The reference for measuring FA is the typical label. . . . . . . . . . . . . seventy two XII record of Tables five. 2 five. three five. four five. five five. 6 five. 7 five. eight FA of the MLPs located on the first hierarchical point while the MLPs are proficient in accordance with the typical label. The reference for measuring FA is additionally the typical label. . . . . . . . . Phoneme attractiveness accuracies of the inter and intra hierarchical schemes. The variety of posterior vectors on the enter of the second one point is M = five masking a temporal context of C = 21 frames. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . body and phoneme accuracies the place the second one hierarchical point corresponds to a SLP. The accuracies are dependent in basic terms on 1-state modeling. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . body and phoneme accuracies of the hierarchical scheme utilizing MLP or SLP on the moment point. . . . . . . . . . . . . . . . . . . . . . body and phoneme accuracy while the temporal context on the enter of the second one hierarchical point corresponds to just one body. . . . .

Download PDF sample

Rated 4.22 of 5 – based on 24 votes