Titlebook: Hierarchical Neural Network Structures for Phoneme Recognition; Daniel Vasquez,Rainer Gruhn,Wolfgang Minker Book 2013 Springer Berlin Heid

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書目名稱Hierarchical Neural Network Structures for Phoneme Recognition影響因子(影響力)




書目名稱Hierarchical Neural Network Structures for Phoneme Recognition影響因子(影響力)學(xué)科排名




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書目名稱Hierarchical Neural Network Structures for Phoneme Recognition讀者反饋




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慢跑鞋

978-3-642-43210-1Springer Berlin Heidelberg 2013

Mercantile

Hierarchical Neural Network Structures for Phoneme Recognition978-3-642-34425-1Series ISSN 1860-4862 Series E-ISSN 1860-4870

使人入神

Daniel Vasquez,Rainer Gruhn,Wolfgang MinkerSimplifies the analysis in spoken language dialogue systems.Investigates hierarchical structures based on neural networks for automatic speech recognition.Written for academic and industrial researche

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Signals and Communication Technologyhttp://image.papertrans.cn/h/image/426142.jpg

我要沮喪

Theoretical Framework for Phoneme Recognition Analysis,y exploited in e.g. ... A common feature extraction method is Linear Prediction Coding (LPC). As it was explained in Section 2.1.1, this method models the speech production based on a finite impulse response (FIR) filter. The impulse response coefficients of the filter are estimated based on the autocorrelation function of the speech signal.

拱形面包

Summary and Conclusions,the area of ASR. Besides being directly related to automatic speech recognition, phoneme recognition has been also applied to speaker recognition, speech detection, language identification, OOV word detection, keyword spotting, among others.

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