منابع مشابه
Eigenvoice Speaker Adaptation via Composite Kernel PCA
Eigenvoice speaker adaptation has been shown to be effective when only a small amount of adaptation data is available. At the heart of the method is principal component analysis (PCA) employed to find the most important eigenvoices. In this paper, we postulate that nonlinear PCA, in particular kernel PCA, may be even more effective. One major challenge is to map the feature-space eigenvoices ba...
متن کاملSpeedup of kernel eigenvoice speaker adaptation by embedded kernel PCA
Recently, we proposed an improvement to the eigenvoice (EV) speaker adaptation called kernel eigenvoice (KEV) speaker adaptation. In KEV adaptation, eigenvoices are computed using kernel PCA, and a new speaker’s adapted model is implicitly computed in the kernel-induced feature space. Due to many online kernel evaluations, both adaptation and subsequent recognition of KEV adaptation are slower ...
متن کاملEigenvoice Speaker Adaptation via Composite Kernel Principal Component Analysis
Eigenvoice speaker adaptation has been shown to be effective when only a small amount of adaptation data is available. At the heart of the method is principal component analysis (PCA) employed to find the most important eigenvoices. In this paper, we postulate that nonlinear PCA, in particular kernel PCA, may be even more effective. One major challenge is to map the feature-space eigenvoices ba...
متن کاملRapid speaker adaptation in eigenvoice space
This paper describes a new model-based speaker adaptation algorithm called the eigenvoice approach. The approach constrains the adapted model to be a linear combination of a small number of basis vectors obtained offline from a set of reference speakers, and thus greatly reduces the number of free parameters to be estimated from adaptation data. These “eigenvoice” basis vectors are orthogonal t...
متن کاملSegmental eigenvoice for rapid speaker adaptation
This paper presents a new approach to improve the conventional eigenvoice technique. In the conventional eigenvoice, an eigenspace is established by introducing a priori training speakers via PCA. The adaptation data is then used to determine a group of coefficients with respect to the eigenspace and build the SD model for the testing speaker. In the proposed approach, the eigenspace in the con...
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ژورنال
عنوان ژورنال: IEEE Transactions on Speech and Audio Processing
سال: 2005
ISSN: 1063-6676
DOI: 10.1109/tsa.2005.851971