Speaker Adaptation in Sparse Subspace of Acoustic Models

Abstract

I propose an acoustic model adaptation method using bases constructed through the sparse principal component analysis (SPCA) of acoustic models trained in a clean environment. I perform experiments on adaptation to a new speaker and noise. The SPCA-based method outperforms the PCA-based method in the presence of babble noise.