Paper Info
Title
Comparing glottal-flow-excited statistical parametric speech synthesis methods
Abstract
This paper studies the performance of glottal flow signal based excitation methods in statistical parametric speech synthesis. The current state of the art in excitationmodeling is reviewed and three excitation methods are selected for experiments. Two of the methods are based on the principal component analysis (PCA) decomposition of estimated glottal flow pulses. While the first one uses only the mean of the pulses, the second method uses 12 principal components in addition to the mean signal for modeling the glottal flow waveform. The third method utilizes a glottal flow pulse library from which pulses are selected according to target and concatenation costs. Subjective listening tests are carried out to determine the quality and similarity of the synthetic speech of one male and one female speaker. The results show that the PCA-based methods are rated best both in quality and similarity, but adding more components does not yield any improvements.
Year
DOI
Venue
2013
10.1109/ICASSP.2013.6639188
Acoustics, Speech and Signal Processing
Keywords
DocType
ISSN
principal component analysis,speaker recognition,speech synthesis,excitation modeling,female speaker,glottal flow pulse library,glottal flow signal based excitation methods,glottal flow waveform,glottal-flow-excited statistical parametric speech synthesis methods,principal component analysis decomposition,statistical parametric speech synthesis,excitation glottal flow,pulse library,speech,noise,hidden markov models
Conference
1520-6149
Citations 
PageRank 
References 
7
0.43
19
Authors
4
Name
Order
Citations
PageRank
Tuomo Raitio114912.86
Antti Suni2879.42
Martti Vainio320925.72
Paavo Alku472898.07