Paper Info
Title
Introducing the Discrete Morphlet Transform and its Applications for Voice Conversion
Abstract
This paper introduces Morph let, a new wavelet transform adapted for voice conversion purposes. The paradigm of joint time-frequency-shape analysis of discrete-time signals, possible by means of the Discrete Shape let Transform (DST), is the basis used for the construction of Morph lets. The results assure the efficacy of the proposed transform, which is able, by itself and with the help of no other tool such as a neural network, to carry out the task, totally.
Year
DOI
Venue
2011
10.1109/ISM.2011.93
Multimedia
Keywords
Field
DocType
discrete morphlet transform,voice conversion,new wavelet,neural network,discrete shape,discrete-time signal,voice conversion purpose,joint time-frequency-shape analysis,speech processing,finite impulse response filter,wavelet transforms,time frequency,wavelet transform,shape,shape analysis,mathematical model,wavelets,discrete time,finite impulse response
Speech processing,Computer vision,Pattern recognition,Computer science,Speech recognition,Artificial intelligence,Artificial neural network,Finite impulse response,Wavelet,Wavelet transform
Conference
ISBN
Citations 
PageRank 
978-1-4577-2015-4
0
0.34
References 
Authors
3
3
Name
Order
Citations
PageRank
Lucimar Sasso Vieira1204.85
Rodrigo Capobianco Guido216127.59
Shi-Huang Chen300.34