Andere Kunden interessierten sich auch für
![Human Face Recognition with Support Vector Machines]( "Human Face Recognition with Support Vector Machines")
Human Face Recognition with Support Vector Machines32,99 €![Scalability Issues of NER using Multi-Class Support Vector Machines]( "Scalability Issues of NER using Multi-Class Support Vector Machines")
Scalability Issues of NER using Multi-Class Support Vector Machines36,99 €![Twin Support Vector Machines]( "Twin Support Vector Machines")
Twin Support Vector Machines74,99 €![Support Vector Machines Applications]( "Support Vector Machines Applications")
Support Vector Machines Applications125,99 €![Large Scale Support Vector Machines Algorithms for Visual Recognition]( "Large Scale Support Vector Machines Algorithms for Visual Recognition")
Large Scale Support Vector Machines Algorithms for Visual Recognition51,99 €![Support Vector Machines and Evolutionary Algorithms for Classification]( "Support Vector Machines and Evolutionary Algorithms for Classification")
Support Vector Machines and Evolutionary Algorithms for Classification74,99 €![Vector Quantization based Speech Recognition System]( "Vector Quantization based Speech Recognition System")
Vector Quantization based Speech Recognition System32,99 €
The book in hand provides the reader with the basics of speech as well as in-depth technicalities of accurate recognition by use of two different artificial intelligence techniques. The literature review presented in a number of chapters, refines user's concepts about the phonetics and mel frequency ceptstral cofficients that characterize speech as well as voice. These coefficients are then operated upon in MATLAB for analysis and classification to one of the predefined classes of a trained system. After reading this book thoroughly the user will be able to conclude that the efficiency of recognition is enhanced when two artificial intelligence or classification techniques, called Linear Discriminant Analysis and Support vector machines, concatenate. This book also gives brief knowledge about the Mercer Kernel, k-nearest neighbor and many other technical concepts.