[PDF.36st] Hierarchical Neural Network Structures for Phoneme Recognition (Signals and Communication Technology)
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Hierarchical Neural Network Structures for Phoneme Recognition (Signals and Communication Technology)
Daniel Vasquez, Rainer Gruhn, Wolfgang Minker
[PDF.fq35] Hierarchical Neural Network Structures for Phoneme Recognition (Signals and Communication Technology)
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| #10481051 in Books | 2014-11-09 | 2014-11-09 | Original language:English | PDF # 1 | 9.25 x.35 x6.10l,.49 | File type: PDF | 134 pages||0 of 0 people found the following review helpful.| Wonderful book|By Mohammed Abdelrahim|This is a really great book on how to make machine learning much more adaptive for dynamic sequential data.|||From the reviews:“This brief book comes packed with useful information about some novel techniques for the recognition of speech building blocks known as phonemes. … it is brimming with useful and well-presented information. I recommend it for gr
The subject of this study is the role of hierarchical structures, based on neural networks, in identifying phonemes in automated speech recognition systems. It shows how the artificial neural network paradigm can simplify the analysis of spoken language.
You easily download any file type for your device.Hierarchical Neural Network Structures for Phoneme Recognition (Signals and Communication Technology) | Daniel Vasquez, Rainer Gruhn, Wolfgang Minker. I have read it a couple of times and even shared with my family members. Really good. Couldnt put it down.
