A study of the relative importance of temporal characteristics in text dependent and text constrained speaker verification

The relative importance of the temporal characteristics of speech for text-dependent and text-constrained speaker verification is investigated. A novel scheme is proposed using a common set of Gaussian components to form various HMM and GMM configurations, establishing a systematic transition from text-dependent to text-constrained speaker verification, and resulting in a novel alternative to conventional GMM-UBM training. Experimental results indicate that the intra-word temporal characteristics of speech do not contribute significantly to performance, however the inter-word temporal characteristics can be used during both enrollment and testing to improve verification performance.